The cl-online-learning Reference Manual

This is the cl-online-learning Reference Manual, version 0.5, generated automatically by Declt version 4.0 beta 2 "William Riker" on Wed May 15 04:19:23 2024 GMT+0.

Table of Contents


1 Introduction


2 Systems

The main system appears first, followed by any subsystem dependency.


2.1 cl-online-learning

Online Machine Learning for Common Lisp

Author

Satoshi Imai

License

MIT Licence

Long Description

* Cl-Online-Learning

[[http://quickdocs.org/cl-online-learning/][http://quickdocs.org/badge/cl-online-learning.svg]]
[[https://github.com/masatoi/cl-online-learning/actions?query=workflow%3ACI][https://github.com/masatoi/cl-online-learning/workflows/CI/badge.svg]]

A collection of machine learning algorithms for online linear classification written in Common Lisp.

** Implemented algorithms

*** Binary classifier
- Perceptron
- AROW (Crammer, Koby, Alex Kulesza, and Mark Dredze. "Adaptive regularization of weight vectors." Advances in neural information processing systems. 2009.)
- SCW-I (Soft Confidence Weighted) (Wang, Jialei, Peilin Zhao, and Steven C. Hoi. "Exact Soft Confidence-Weighted Learning." Proceedings of the 29th International Conference on Machine Learning (ICML-12). 2012.)
- Logistic Regression with SGD or ADAM optimizer (Kingma, Diederik, and Jimmy Ba. "Adam: A method for stochastic optimization." ICLR 2015)

*** Multiclass classifier
- one-vs-rest ( K binary classifier required )
- one-vs-one ( K*(K-1)/2 binary classifier required )

*** Command line tools
- Implemented as roswell script
- See https://github.com/masatoi/cl-online-learning/wiki/Using-as-command-line-tools

** Installation
cl-online-learning is available from Quicklisp.
#+BEGIN_SRC
(ql:quickload :cl-online-learning)
#+END_SRC

When install from github repository,
#+BEGIN_SRC
cd ~/quicklisp/local-projects/
git clone https://github.com/masatoi/cl-online-learning.git
#+END_SRC
When using Roswell,
#+BEGIN_SRC
ros install masatoi/cl-online-learning
#+END_SRC
** Usage
*** Prepare dataset
A data point is a pair of a class label (+1 or -1) and a input vector. Both of them have to be declared as single-float.

And dataset is represented as a sequence of data points.
READ-DATA function is available to make a dataset from a sparse format used in LIBSVM (http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/). This function requires the number of features of that dataset.
#+BEGIN_SRC lisp
;; Number of features
(defparameter a1a-dim 123)

;; Read dataset from file
(defparameter a1a
(clol.utils:read-data
(merge-pathnames #P"t/dataset/a1a" (asdf:system-source-directory :cl-online-learning))
a1a-dim))

;; A data point
(car a1a)

; (-1.0
; . #(0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0
; 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
; 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
; 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0
; 1.0 0.0 1.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
; 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
; 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0))
#+END_SRC

*** Define learner
A learner object is just a struct, therefore their constructor is available to make it.
#+BEGIN_SRC lisp
(defparameter arow-learner (clol:make-arow a1a-dim 10))
#+END_SRC

*** Update and Train
To update the model destructively with one data point, use an update function corresponding to the model type.
#+BEGIN_SRC lisp
(clol:arow-update arow-learner
(cdar a1a) ; input
(caar a1a)) ; label
#+END_SRC
TRAIN function can be used to learn the dataset collectively.
#+BEGIN_SRC lisp
(clol:train arow-learner a1a)
#+END_SRC
It may be necessary to call this function several times until learning converges. For now, the convergence test has not been implemented yet.

*** Predict and Test
#+BEGIN_SRC lisp
(clol:arow-predict arow-learner (cdar a1a))
; => -1.0

(clol:test arow-learner a1a)
; Accuracy: 84.85981%, Correct: 1362, Total: 1605
#+END_SRC

*** Multiclass classification
For multiclass data, the label of the data point is an integer representing the index of the class. READ-DATA function with MULTICLASS-P keyword option is available for make such a dataset.
#+BEGIN_SRC lisp
(defparameter iris-dim 4)

; A dataset in which a same label appears consecutively need to be shuffled
(defparameter iris
(clol.utils:shuffle-vector
(coerce (clol.utils:read-data
(merge-pathnames #P"t/dataset/iris.scale"
(asdf:system-source-directory :cl-online-learning))
iris-dim :multiclass-p t)
’simple-vector)))

(defparameter iris-train (subseq iris 0 100))
(defparameter iris-test (subseq iris 100))
#+END_SRC
ONE-VS-REST and ONE-VS-ONE are available for multiclass classification by using multiple binary classifiers. In many cases, ONE-VS-ONE is more accurate, but it requires more computational resource as the number of classes increases.
#+BEGIN_SRC lisp
;; Define model
(defparameter arow-1vs1
(clol:make-one-vs-one iris-dim ; Input data dimension
3 ; Number of class
’arow 0.1)) ; Binary classifier type and its parameters

;; Train and test model
(clol:train arow-1vs1 iris-train)
(clol:test arow-1vs1 iris-test)
; Accuracy: 98.0%, Correct: 49, Total: 50
#+END_SRC

*** Sparse data
For sparse data (most elements are 0), the data point is a pair of a class label and a instance of SPARSE-VECTOR struct, and a learner with SPARSE- prefix is used. READ-DATA function with SPARSE-P keyword option is available for make such a dataset.

For example, news20.binary data has too high dimensional features to handle with normal learners. However, by using the sparse version, the learner can be trained with practical computational resources.
#+BEGIN_SRC lisp
(defparameter news20.binary-dim 1355191)
(defparameter news20.binary (clol.utils:read-data "/path/to/news20.binary" news20.binary-dim :sparse-p t))

(defparameter news20.binary.arow (clol:make-sparse-arow news20.binary-dim 10))
(time (loop repeat 20 do (clol:train news20.binary.arow news20.binary)))
;; Evaluation took:
;; 1.527 seconds of real time
;; 1.526852 seconds of total run time (1.526852 user, 0.000000 system)
;; 100.00% CPU
;; 5,176,917,149 processor cycles
;; 11,436,032 bytes consed
(clol:test news20.binary.arow news20.binary)
; Accuracy: 99.74495%, Correct: 19945, Total: 19996
#+END_SRC

In a similar way, the sparse version learners are also available in multiclass classification.

#+BEGIN_SRC lisp
(defparameter news20-dim 62060)
(defparameter news20-train (clol.utils:read-data "/path/to/news20.scale" news20-dim :sparse-p t :multiclass-p t))
(defparameter news20-test (clol.utils:read-data "/path/to/news20.t.scale" news20-dim :sparse-p t :multiclass-p t))
(defparameter news20-arow (clol:make-one-vs-rest news20-dim 20 ’sparse-arow 10))
(loop repeat 12 do (clol:train news20-arow news20-train))
(clol:test news20-arow news20-test)
; Accuracy: 86.90208%, Correct: 3470, Total: 3993
#+END_SRC

# *** Benchimark

*** Save/Restore model
For saving a learner model to a file or restoring from the model file, SAVE and RESTORE function are available respectively.
For the above multiclass classification example, saving / restoring code would be:

#+BEGIN_SRC lisp
;; Save
(clol:save arow-1vs1 #P"/tmp/iris.model")
;; Restore
(defparameter restored-learner (clol:restore #P"/tmp/iris.model"))

(clol:test restored-learner iris-test)
; Accuracy: 98.0%, Correct: 49, Total: 50
#+END_SRC

** Author
Satoshi Imai (satoshi.imai@gmail.com)

** Licence
This software is released under the MIT License, see LICENSE.txt.

Version

0.5

Dependencies
  • cl-libsvm-format (system).
  • cl-store (system).
Source

cl-online-learning.asd.

Child Component

src (module).


3 Modules

Modules are listed depth-first from the system components tree.


3.1 cl-online-learning/src

Source

cl-online-learning.asd.

Parent Component

cl-online-learning (system).

Child Components

4 Files

Files are sorted by type and then listed depth-first from the systems components trees.


4.1 Lisp


4.1.1 cl-online-learning/cl-online-learning.asd

Source

cl-online-learning.asd.

Parent Component

cl-online-learning (system).

ASDF Systems

cl-online-learning.

Packages

cl-online-learning-asd.


4.1.2 cl-online-learning/src/vector.lisp

Source

cl-online-learning.asd.

Parent Component

src (module).

Packages

cl-online-learning.vector.

Public Interface
Internals

4.1.3 cl-online-learning/src/utils.lisp

Dependency

vector.lisp (file).

Source

cl-online-learning.asd.

Parent Component

src (module).

Packages

cl-online-learning.utils.

Public Interface
Internals

4.1.4 cl-online-learning/src/cl-online-learning.lisp

Dependency

vector.lisp (file).

Source

cl-online-learning.asd.

Parent Component

src (module).

Packages

cl-online-learning.

Public Interface
Internals

4.1.5 cl-online-learning/src/rls.lisp

Dependencies
Source

cl-online-learning.asd.

Parent Component

src (module).

Public Interface
Internals

5 Packages

Packages are listed by definition order.


5.1 cl-online-learning-asd

Source

cl-online-learning.asd.

Use List
  • asdf/interface.
  • common-lisp.

5.2 cl-online-learning.utils

Source

utils.lisp.

Nickname

clol.utils

Use List
Public Interface
Internals

5.3 cl-online-learning

Source

cl-online-learning.lisp.

Nickname

clol

Use List
Public Interface
Internals

5.4 cl-online-learning.vector

Source

vector.lisp.

Nickname

clol.vector

Use List

common-lisp.

Used By List
Public Interface
Internals

6 Definitions

Definitions are sorted by export status, category, package, and then by lexicographic order.


6.1 Public Interface


6.1.1 Macros

Macro: defmain (lambda-list &body body)
Package

cl-online-learning.utils.

Source

utils.lisp.

Macro: dosvec (svec var &body body)
Package

cl-online-learning.vector.

Source

vector.lisp.

Macro: dovec (vec var &body body)
Package

cl-online-learning.vector.

Source

vector.lisp.


6.1.2 Ordinary functions

Function: arow-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: arow-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: arow-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: arow-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: class-min/max (read-data-result)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: dim-of (learner)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: dot (x y)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: dot! (x y result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: dps-v* (dence-x pseudosparse-y index-vector result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: dps-v+ (dence-x pseudosparse-y index-vector result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: dps-v- (dence-x pseudosparse-y index-vector result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: ds-dot (dence-x sparse-y)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: ds-dot! (dence-x sparse-y result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: ds-v* (dence-x sparse-y result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: ds-v+ (dence-x sparse-y result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: ds-v- (dence-x sparse-y result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: ds-v/ (dence-x sparse-y result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: ds2s-v* (dence-x sparse-y sparse-result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: lr+adam-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: lr+adam-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: lr+adam-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: lr+adam-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: lr+sgd-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: lr+sgd-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: lr+sgd-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: lr+sgd-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-arow (input-dimension gamma)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-empty-sparse-vector (sparse-dim)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: make-lr+adam (input-dimension c alpha epsilon beta1 beta2)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-lr+sgd (input-dimension c eta)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-one-vs-one (input-dimension n-class learner-type &rest learner-params)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-one-vs-rest (input-dimension n-class learner-type &rest learner-params)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-perceptron (input-dimension)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-rls (input-dimension gamma)
Package

cl-online-learning.

Source

rls.lisp.

Function: make-scw (input-dimension eta c)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-sparse-arow (input-dimension gamma)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-sparse-lr+adam (input-dimension c alpha epsilon beta1 beta2)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-sparse-lr+sgd (input-dimension c eta)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-sparse-perceptron (input-dimension)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-sparse-rls (input-dimension gamma)
Package

cl-online-learning.

Source

rls.lisp.

Function: make-sparse-scw (input-dimension eta c)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: make-sparse-vector (index-vector value-vector)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: make-vec (input-dimension initial-element)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: n-class-of (learner)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-one-predict (mulc input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-one-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-one-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-one-update (mulc input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-rest-predict (mulc input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-rest-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-rest-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-rest-update (mulc input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: perceptron-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: perceptron-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: perceptron-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: perceptron-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: ps-v*n (pseudosparse-x n index-vector result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: read-data (data-path data-dimension &key multiclass-p sparse-p)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: restore (file-path)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: rls-predict (learner input)
Package

cl-online-learning.

Source

rls.lisp.

Function: rls-test (learner test-data &key quiet-p)
Package

cl-online-learning.

Source

rls.lisp.

Function: rls-train (learner training-data)
Package

cl-online-learning.

Source

rls.lisp.

Function: rls-update (learner input target)
Package

cl-online-learning.

Source

rls.lisp.

Function: s-v*n (sparse-x n result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: save (learner file-path)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: scw-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: scw-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: scw-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: scw-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: shuffle-vector (vec)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: sparse-arow-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-arow-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-arow-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-arow-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-learner? (learner)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-lr+adam-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-lr+adam-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-lr+adam-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-lr+adam-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-lr+sgd-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-lr+sgd-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-lr+sgd-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-lr+sgd-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-perceptron-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-perceptron-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-perceptron-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-perceptron-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-rls-predict (learner input)
Package

cl-online-learning.

Source

rls.lisp.

Function: sparse-rls-test (learner test-data &key quiet-p)
Package

cl-online-learning.

Source

rls.lisp.

Function: sparse-rls-train (learner training-data)
Package

cl-online-learning.

Source

rls.lisp.

Function: sparse-rls-update (learner input target)
Package

cl-online-learning.

Source

rls.lisp.

Function: sparse-scw-predict (learner input)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-scw-test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-scw-train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-scw-update (learner input training-label)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: sparse-vector-index-vector (instance)
Writer: (setf sparse-vector-index-vector) (instance)
Package

cl-online-learning.vector.

Source

vector.lisp.

Target Slot

index-vector.

Reader: sparse-vector-length (instance)
Writer: (setf sparse-vector-length) (instance)
Package

cl-online-learning.vector.

Source

vector.lisp.

Target Slot

length.

Reader: sparse-vector-value-vector (instance)
Writer: (setf sparse-vector-value-vector) (instance)
Package

cl-online-learning.vector.

Source

vector.lisp.

Target Slot

value-vector.

Function: sps-v*n (sparse-x n result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: test (learner test-data &key quiet-p stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: to-float (x)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: to-int (x)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: train (learner training-data)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: v* (x y result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: v*n (vec n result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: v+ (x y result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: v+n (x n result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: v- (x y result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: v-sqrt (x result)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: v/ (x y result)
Package

cl-online-learning.vector.

Source

vector.lisp.


6.1.3 Standalone methods

Method: print-object ((object sparse-scw) stream)
Source

cl-online-learning.lisp.

Method: print-object ((object perceptron) stream)
Source

cl-online-learning.lisp.

Method: print-object ((object rls) stream)
Source

rls.lisp.

Method: print-object ((object one-vs-rest) stream)
Source

cl-online-learning.lisp.

Method: print-object ((object arow) stream)
Source

cl-online-learning.lisp.

Method: print-object ((object one-vs-one) stream)
Source

cl-online-learning.lisp.

Method: print-object ((object lr+adam) stream)
Source

cl-online-learning.lisp.

Method: print-object ((object sparse-lr+adam) stream)
Source

cl-online-learning.lisp.

Method: print-object ((object sparse-rls) stream)
Source

rls.lisp.

Method: print-object ((object scw) stream)
Source

cl-online-learning.lisp.

Method: print-object ((object sparse-arow) stream)
Source

cl-online-learning.lisp.

Method: print-object ((object sparse-perceptron) stream)
Source

cl-online-learning.lisp.


6.1.4 Structures

Structure: sparse-vector
Package

cl-online-learning.vector.

Source

vector.lisp.

Direct superclasses

structure-object.

Direct slots
Slot: length
Package

common-lisp.

Type

fixnum

Initform

0

Readers

sparse-vector-length.

Writers

(setf sparse-vector-length).

Slot: index-vector
Type

(simple-array fixnum)

Initform

#()

Readers

sparse-vector-index-vector.

Writers

(setf sparse-vector-index-vector).

Slot: value-vector
Type

(simple-array single-float)

Initform

#()

Readers

sparse-vector-value-vector.

Writers

(setf sparse-vector-value-vector).


6.2 Internals


6.2.1 Macros

Macro: catstr (str1 str2)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Macro: define-learner (learner-type (learner input training-label) &body body)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Macro: define-multi-class-learner-train/test-functions (learner-type)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Macro: define-regression-learner (learner-type (learner input target) &body body)
Package

cl-online-learning.

Source

rls.lisp.

Macro: doseq ((var seq) &body body)
Package

cl-online-learning.utils.

Source

utils.lisp.

Macro: function-by-name (name-string)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Macro: sigmoid (x)
Package

cl-online-learning.

Source

cl-online-learning.lisp.


6.2.2 Ordinary functions

Function: %make-arow (&key input-dimension weight bias gamma sigma sigma0 tmp-vec1 tmp-vec2 tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-lr+adam (&key input-dimension weight bias c alpha epsilon beta1 beta2 g m v m0 v0 beta1^t beta2^t tmp-vec tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-lr+sgd (&key input-dimension weight bias c eta g tmp-vec tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-one-vs-one (&key input-dimension n-class learners-vector learner-update learner-predict)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-one-vs-rest (&key input-dimension n-class learners-vector learner-weight learner-bias learner-update learner-activate)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-perceptron (&key input-dimension weight bias tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-rls (&key input-dimension weight bias gamma sigma sigma0 tmp-vec1 tmp-vec2 tmp-float)
Package

cl-online-learning.

Source

rls.lisp.

Function: %make-scw (&key input-dimension weight bias eta c phi psi zeta sigma sigma0 tmp-vec1 tmp-vec2 tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-sparse-arow (&key input-dimension weight bias gamma sigma sigma0 tmp-vec1 tmp-vec2 tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-sparse-lr+adam (&key input-dimension weight bias c alpha epsilon beta1 beta2 g m v m0 v0 beta1^t beta2^t tmp-vec tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-sparse-lr+sgd (&key input-dimension weight bias c eta g tmp-vec tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-sparse-perceptron (&key input-dimension weight bias tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-sparse-rls (&key input-dimension weight bias gamma sigma sigma0 tmp-vec1 tmp-vec2 tmp-float)
Package

cl-online-learning.

Source

rls.lisp.

Function: %make-sparse-scw (&key input-dimension weight bias eta c phi psi zeta sigma sigma0 tmp-vec1 tmp-vec2 tmp-float)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %make-sparse-vector (&key length index-vector value-vector)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: %print-arow (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %print-lr+adam (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %print-one-vs-one (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %print-one-vs-rest (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %print-perceptron (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %print-rls (obj stream)
Package

cl-online-learning.

Source

rls.lisp.

Function: %print-scw (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %print-sparse-arow (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %print-sparse-lr+adam (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %print-sparse-perceptron (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: %print-sparse-rls (obj stream)
Package

cl-online-learning.

Source

rls.lisp.

Function: %print-sparse-scw (obj stream)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: arg-list->lambda-arg (arg-list)
Package

cl-online-learning.utils.

Source

utils.lisp.

Reader: arow-bias (instance)
Writer: (setf arow-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: arow-gamma (instance)
Writer: (setf arow-gamma) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

gamma.

Reader: arow-input-dimension (instance)
Writer: (setf arow-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Function: arow-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: arow-sigma (instance)
Writer: (setf arow-sigma) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

sigma.

Reader: arow-sigma0 (instance)
Writer: (setf arow-sigma0) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

sigma0.

Reader: arow-tmp-float (instance)
Writer: (setf arow-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: arow-tmp-vec1 (instance)
Writer: (setf arow-tmp-vec1) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec1.

Reader: arow-tmp-vec2 (instance)
Writer: (setf arow-tmp-vec2) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec2.

Reader: arow-weight (instance)
Writer: (setf arow-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Function: copy-arow (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-lr+adam (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-lr+sgd (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-one-vs-one (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-one-vs-rest (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-perceptron (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-rls (instance)
Package

cl-online-learning.

Source

rls.lisp.

Function: copy-scw (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-sparse-arow (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-sparse-lr+adam (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-sparse-lr+sgd (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-sparse-perceptron (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-sparse-rls (instance)
Package

cl-online-learning.

Source

rls.lisp.

Function: copy-sparse-scw (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: copy-sparse-vector (instance)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: f (input weight bias)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: f! (input weight bias result)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: flatten (structure)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: group-arg-list (arg-list)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: index-of-learner (k i l)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: inverse-erf (x)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: logistic-regression-gradient! (training-label input-vector weight-vector bias c tmp-vec g-result g0-result)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: logistic-regression-gradient-sparse! (training-label input-vector weight-vector bias c tmp-vec g-result g0-result)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: lr+adam-alpha (instance)
Writer: (setf lr+adam-alpha) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

alpha.

Reader: lr+adam-beta1 (instance)
Writer: (setf lr+adam-beta1) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

beta1.

Reader: lr+adam-beta1^t (instance)
Writer: (setf lr+adam-beta1^t) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

beta1^t.

Reader: lr+adam-beta2 (instance)
Writer: (setf lr+adam-beta2) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

beta2.

Reader: lr+adam-beta2^t (instance)
Writer: (setf lr+adam-beta2^t) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

beta2^t.

Reader: lr+adam-bias (instance)
Writer: (setf lr+adam-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: lr+adam-c (instance)
Writer: (setf lr+adam-c) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

c.

Reader: lr+adam-epsilon (instance)
Writer: (setf lr+adam-epsilon) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

epsilon.

Reader: lr+adam-g (instance)
Writer: (setf lr+adam-g) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

g.

Reader: lr+adam-input-dimension (instance)
Writer: (setf lr+adam-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Reader: lr+adam-m (instance)
Writer: (setf lr+adam-m) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

m.

Reader: lr+adam-m0 (instance)
Writer: (setf lr+adam-m0) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

m0.

Function: lr+adam-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: lr+adam-tmp-float (instance)
Writer: (setf lr+adam-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: lr+adam-tmp-vec (instance)
Writer: (setf lr+adam-tmp-vec) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec.

Reader: lr+adam-v (instance)
Writer: (setf lr+adam-v) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

v.

Reader: lr+adam-v0 (instance)
Writer: (setf lr+adam-v0) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

v0.

Reader: lr+adam-weight (instance)
Writer: (setf lr+adam-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Reader: lr+sgd-bias (instance)
Writer: (setf lr+sgd-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: lr+sgd-c (instance)
Writer: (setf lr+sgd-c) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

c.

Reader: lr+sgd-eta (instance)
Writer: (setf lr+sgd-eta) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

eta.

Reader: lr+sgd-g (instance)
Writer: (setf lr+sgd-g) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

g.

Reader: lr+sgd-input-dimension (instance)
Writer: (setf lr+sgd-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Function: lr+sgd-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: lr+sgd-tmp-float (instance)
Writer: (setf lr+sgd-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: lr+sgd-tmp-vec (instance)
Writer: (setf lr+sgd-tmp-vec) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec.

Reader: lr+sgd-weight (instance)
Writer: (setf lr+sgd-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Function: mean-vector (dataset)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: one-vs-one-clear-functions-for-store (mulc)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: one-vs-one-input-dimension (instance)
Writer: (setf one-vs-one-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Reader: one-vs-one-learner-predict (instance)
Writer: (setf one-vs-one-learner-predict) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

learner-predict.

Reader: one-vs-one-learner-update (instance)
Writer: (setf one-vs-one-learner-update) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

learner-update.

Reader: one-vs-one-learners-vector (instance)
Writer: (setf one-vs-one-learners-vector) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

learners-vector.

Reader: one-vs-one-n-class (instance)
Writer: (setf one-vs-one-n-class) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

n-class.

Function: one-vs-one-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-one-restore-functions (mulc)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-rest-clear-functions-for-store (mulc)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: one-vs-rest-input-dimension (instance)
Writer: (setf one-vs-rest-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Reader: one-vs-rest-learner-activate (instance)
Writer: (setf one-vs-rest-learner-activate) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

learner-activate.

Reader: one-vs-rest-learner-bias (instance)
Writer: (setf one-vs-rest-learner-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

learner-bias.

Reader: one-vs-rest-learner-update (instance)
Writer: (setf one-vs-rest-learner-update) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

learner-update.

Reader: one-vs-rest-learner-weight (instance)
Writer: (setf one-vs-rest-learner-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

learner-weight.

Reader: one-vs-rest-learners-vector (instance)
Writer: (setf one-vs-rest-learners-vector) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

learners-vector.

Reader: one-vs-rest-n-class (instance)
Writer: (setf one-vs-rest-n-class) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

n-class.

Function: one-vs-rest-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: one-vs-rest-restore-functions (mulc)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: perceptron-bias (instance)
Writer: (setf perceptron-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: perceptron-input-dimension (instance)
Writer: (setf perceptron-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Function: perceptron-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: perceptron-tmp-float (instance)
Writer: (setf perceptron-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: perceptron-weight (instance)
Writer: (setf perceptron-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Function: probit (p)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: read-datum (svmformat-datum data-dimension &key multiclass-p)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: read-datum-sparse (svmformat-datum &key multiclass-p)
Package

cl-online-learning.utils.

Source

utils.lisp.

Reader: rls-bias (instance)
Writer: (setf rls-bias) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

bias.

Reader: rls-gamma (instance)
Writer: (setf rls-gamma) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

gamma.

Reader: rls-input-dimension (instance)
Writer: (setf rls-input-dimension) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

input-dimension.

Function: rls-p (object)
Package

cl-online-learning.

Source

rls.lisp.

Reader: rls-sigma (instance)
Writer: (setf rls-sigma) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

sigma.

Reader: rls-sigma0 (instance)
Writer: (setf rls-sigma0) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

sigma0.

Reader: rls-tmp-float (instance)
Writer: (setf rls-tmp-float) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

tmp-float.

Reader: rls-tmp-vec1 (instance)
Writer: (setf rls-tmp-vec1) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

tmp-vec1.

Reader: rls-tmp-vec2 (instance)
Writer: (setf rls-tmp-vec2) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

tmp-vec2.

Reader: rls-weight (instance)
Writer: (setf rls-weight) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

weight.

Function: sanity-check (lambda-list arg-list)
Package

cl-online-learning.utils.

Source

utils.lisp.

Reader: scw-bias (instance)
Writer: (setf scw-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: scw-c (instance)
Writer: (setf scw-c) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

c.

Reader: scw-eta (instance)
Writer: (setf scw-eta) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

eta.

Reader: scw-input-dimension (instance)
Writer: (setf scw-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Function: scw-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: scw-phi (instance)
Writer: (setf scw-phi) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

phi.

Reader: scw-psi (instance)
Writer: (setf scw-psi) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

psi.

Reader: scw-sigma (instance)
Writer: (setf scw-sigma) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

sigma.

Reader: scw-sigma0 (instance)
Writer: (setf scw-sigma0) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

sigma0.

Reader: scw-tmp-float (instance)
Writer: (setf scw-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: scw-tmp-vec1 (instance)
Writer: (setf scw-tmp-vec1) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec1.

Reader: scw-tmp-vec2 (instance)
Writer: (setf scw-tmp-vec2) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec2.

Reader: scw-weight (instance)
Writer: (setf scw-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Reader: scw-zeta (instance)
Writer: (setf scw-zeta) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

zeta.

Function: sf (input weight bias)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sf! (input weight bias result)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sign (x)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: sparse-arow-bias (instance)
Writer: (setf sparse-arow-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: sparse-arow-gamma (instance)
Writer: (setf sparse-arow-gamma) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

gamma.

Reader: sparse-arow-input-dimension (instance)
Writer: (setf sparse-arow-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Function: sparse-arow-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: sparse-arow-sigma (instance)
Writer: (setf sparse-arow-sigma) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

sigma.

Reader: sparse-arow-sigma0 (instance)
Writer: (setf sparse-arow-sigma0) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

sigma0.

Reader: sparse-arow-tmp-float (instance)
Writer: (setf sparse-arow-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: sparse-arow-tmp-vec1 (instance)
Writer: (setf sparse-arow-tmp-vec1) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec1.

Reader: sparse-arow-tmp-vec2 (instance)
Writer: (setf sparse-arow-tmp-vec2) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec2.

Reader: sparse-arow-weight (instance)
Writer: (setf sparse-arow-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Reader: sparse-lr+adam-alpha (instance)
Writer: (setf sparse-lr+adam-alpha) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

alpha.

Reader: sparse-lr+adam-beta1 (instance)
Writer: (setf sparse-lr+adam-beta1) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

beta1.

Reader: sparse-lr+adam-beta1^t (instance)
Writer: (setf sparse-lr+adam-beta1^t) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

beta1^t.

Reader: sparse-lr+adam-beta2 (instance)
Writer: (setf sparse-lr+adam-beta2) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

beta2.

Reader: sparse-lr+adam-beta2^t (instance)
Writer: (setf sparse-lr+adam-beta2^t) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

beta2^t.

Reader: sparse-lr+adam-bias (instance)
Writer: (setf sparse-lr+adam-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: sparse-lr+adam-c (instance)
Writer: (setf sparse-lr+adam-c) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

c.

Reader: sparse-lr+adam-epsilon (instance)
Writer: (setf sparse-lr+adam-epsilon) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

epsilon.

Reader: sparse-lr+adam-g (instance)
Writer: (setf sparse-lr+adam-g) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

g.

Reader: sparse-lr+adam-input-dimension (instance)
Writer: (setf sparse-lr+adam-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Reader: sparse-lr+adam-m (instance)
Writer: (setf sparse-lr+adam-m) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

m.

Reader: sparse-lr+adam-m0 (instance)
Writer: (setf sparse-lr+adam-m0) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

m0.

Function: sparse-lr+adam-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: sparse-lr+adam-tmp-float (instance)
Writer: (setf sparse-lr+adam-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: sparse-lr+adam-tmp-vec (instance)
Writer: (setf sparse-lr+adam-tmp-vec) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec.

Reader: sparse-lr+adam-v (instance)
Writer: (setf sparse-lr+adam-v) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

v.

Reader: sparse-lr+adam-v0 (instance)
Writer: (setf sparse-lr+adam-v0) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

v0.

Reader: sparse-lr+adam-weight (instance)
Writer: (setf sparse-lr+adam-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Reader: sparse-lr+sgd-bias (instance)
Writer: (setf sparse-lr+sgd-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: sparse-lr+sgd-c (instance)
Writer: (setf sparse-lr+sgd-c) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

c.

Reader: sparse-lr+sgd-eta (instance)
Writer: (setf sparse-lr+sgd-eta) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

eta.

Reader: sparse-lr+sgd-g (instance)
Writer: (setf sparse-lr+sgd-g) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

g.

Reader: sparse-lr+sgd-input-dimension (instance)
Writer: (setf sparse-lr+sgd-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Function: sparse-lr+sgd-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: sparse-lr+sgd-tmp-float (instance)
Writer: (setf sparse-lr+sgd-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: sparse-lr+sgd-tmp-vec (instance)
Writer: (setf sparse-lr+sgd-tmp-vec) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec.

Reader: sparse-lr+sgd-weight (instance)
Writer: (setf sparse-lr+sgd-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Reader: sparse-perceptron-bias (instance)
Writer: (setf sparse-perceptron-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: sparse-perceptron-input-dimension (instance)
Writer: (setf sparse-perceptron-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Function: sparse-perceptron-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: sparse-perceptron-tmp-float (instance)
Writer: (setf sparse-perceptron-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: sparse-perceptron-weight (instance)
Writer: (setf sparse-perceptron-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Reader: sparse-rls-bias (instance)
Writer: (setf sparse-rls-bias) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

bias.

Reader: sparse-rls-gamma (instance)
Writer: (setf sparse-rls-gamma) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

gamma.

Reader: sparse-rls-input-dimension (instance)
Writer: (setf sparse-rls-input-dimension) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

input-dimension.

Function: sparse-rls-p (object)
Package

cl-online-learning.

Source

rls.lisp.

Reader: sparse-rls-sigma (instance)
Writer: (setf sparse-rls-sigma) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

sigma.

Reader: sparse-rls-sigma0 (instance)
Writer: (setf sparse-rls-sigma0) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

sigma0.

Reader: sparse-rls-tmp-float (instance)
Writer: (setf sparse-rls-tmp-float) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

tmp-float.

Reader: sparse-rls-tmp-vec1 (instance)
Writer: (setf sparse-rls-tmp-vec1) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

tmp-vec1.

Reader: sparse-rls-tmp-vec2 (instance)
Writer: (setf sparse-rls-tmp-vec2) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

tmp-vec2.

Reader: sparse-rls-weight (instance)
Writer: (setf sparse-rls-weight) (instance)
Package

cl-online-learning.

Source

rls.lisp.

Target Slot

weight.

Reader: sparse-scw-bias (instance)
Writer: (setf sparse-scw-bias) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

bias.

Reader: sparse-scw-c (instance)
Writer: (setf sparse-scw-c) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

c.

Reader: sparse-scw-eta (instance)
Writer: (setf sparse-scw-eta) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

eta.

Reader: sparse-scw-input-dimension (instance)
Writer: (setf sparse-scw-input-dimension) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

input-dimension.

Function: sparse-scw-p (object)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Reader: sparse-scw-phi (instance)
Writer: (setf sparse-scw-phi) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

phi.

Reader: sparse-scw-psi (instance)
Writer: (setf sparse-scw-psi) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

psi.

Reader: sparse-scw-sigma (instance)
Writer: (setf sparse-scw-sigma) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

sigma.

Reader: sparse-scw-sigma0 (instance)
Writer: (setf sparse-scw-sigma0) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

sigma0.

Reader: sparse-scw-tmp-float (instance)
Writer: (setf sparse-scw-tmp-float) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-float.

Reader: sparse-scw-tmp-vec1 (instance)
Writer: (setf sparse-scw-tmp-vec1) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec1.

Reader: sparse-scw-tmp-vec2 (instance)
Writer: (setf sparse-scw-tmp-vec2) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

tmp-vec2.

Reader: sparse-scw-weight (instance)
Writer: (setf sparse-scw-weight) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

weight.

Reader: sparse-scw-zeta (instance)
Writer: (setf sparse-scw-zeta) (instance)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Target Slot

zeta.

Function: sparse-symbol? (symbol)
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Function: sparse-vector-p (object)
Package

cl-online-learning.vector.

Source

vector.lisp.

Function: split-lambda-list (lambda-list)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: standard-deviation-vector (dataset)
Package

cl-online-learning.utils.

Source

utils.lisp.

Function: sum-permutation (n m)
Package

cl-online-learning.

Source

cl-online-learning.lisp.


6.2.3 Generic functions

Generic Reader: argument-error-message (condition)
Generic Writer: (setf argument-error-message) (condition)
Package

cl-online-learning.utils.

Methods
Reader Method: argument-error-message ((condition argument-error))
Writer Method: (setf argument-error-message) ((condition argument-error))
Source

utils.lisp.

Target Slot

argument-error-message.


6.2.4 Conditions

Condition: argument-error
Package

cl-online-learning.utils.

Source

utils.lisp.

Direct superclasses

simple-error.

Direct methods
Direct slots
Slot: argument-error-message
Initform

(quote nil)

Initargs

:argument-error-message

Readers

argument-error-message.

Writers

(setf argument-error-message).


6.2.5 Structures

Structure: arow
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

arow-input-dimension.

Writers

(setf arow-input-dimension).

Slot: weight
Readers

arow-weight.

Writers

(setf arow-weight).

Slot: bias
Readers

arow-bias.

Writers

(setf arow-bias).

Slot: gamma
Readers

arow-gamma.

Writers

(setf arow-gamma).

Slot: sigma
Readers

arow-sigma.

Writers

(setf arow-sigma).

Slot: sigma0
Readers

arow-sigma0.

Writers

(setf arow-sigma0).

Slot: tmp-vec1
Readers

arow-tmp-vec1.

Writers

(setf arow-tmp-vec1).

Slot: tmp-vec2
Readers

arow-tmp-vec2.

Writers

(setf arow-tmp-vec2).

Slot: tmp-float
Readers

arow-tmp-float.

Writers

(setf arow-tmp-float).

Structure: lr+adam
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

lr+adam-input-dimension.

Writers

(setf lr+adam-input-dimension).

Slot: weight
Readers

lr+adam-weight.

Writers

(setf lr+adam-weight).

Slot: bias
Readers

lr+adam-bias.

Writers

(setf lr+adam-bias).

Slot: c
Readers

lr+adam-c.

Writers

(setf lr+adam-c).

Slot: alpha
Readers

lr+adam-alpha.

Writers

(setf lr+adam-alpha).

Slot: epsilon
Readers

lr+adam-epsilon.

Writers

(setf lr+adam-epsilon).

Slot: beta1
Readers

lr+adam-beta1.

Writers

(setf lr+adam-beta1).

Slot: beta2
Readers

lr+adam-beta2.

Writers

(setf lr+adam-beta2).

Slot: g
Readers

lr+adam-g.

Writers

(setf lr+adam-g).

Slot: m
Readers

lr+adam-m.

Writers

(setf lr+adam-m).

Slot: v
Readers

lr+adam-v.

Writers

(setf lr+adam-v).

Slot: m0
Readers

lr+adam-m0.

Writers

(setf lr+adam-m0).

Slot: v0
Readers

lr+adam-v0.

Writers

(setf lr+adam-v0).

Slot: beta1^t
Readers

lr+adam-beta1^t.

Writers

(setf lr+adam-beta1^t).

Slot: beta2^t
Readers

lr+adam-beta2^t.

Writers

(setf lr+adam-beta2^t).

Slot: tmp-vec
Readers

lr+adam-tmp-vec.

Writers

(setf lr+adam-tmp-vec).

Slot: tmp-float
Readers

lr+adam-tmp-float.

Writers

(setf lr+adam-tmp-float).

Structure: lr+sgd
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct slots
Slot: input-dimension
Readers

lr+sgd-input-dimension.

Writers

(setf lr+sgd-input-dimension).

Slot: weight
Readers

lr+sgd-weight.

Writers

(setf lr+sgd-weight).

Slot: bias
Readers

lr+sgd-bias.

Writers

(setf lr+sgd-bias).

Slot: c
Readers

lr+sgd-c.

Writers

(setf lr+sgd-c).

Slot: eta
Readers

lr+sgd-eta.

Writers

(setf lr+sgd-eta).

Slot: g
Readers

lr+sgd-g.

Writers

(setf lr+sgd-g).

Slot: tmp-vec
Readers

lr+sgd-tmp-vec.

Writers

(setf lr+sgd-tmp-vec).

Slot: tmp-float
Readers

lr+sgd-tmp-float.

Writers

(setf lr+sgd-tmp-float).

Structure: one-vs-one
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

one-vs-one-input-dimension.

Writers

(setf one-vs-one-input-dimension).

Slot: n-class
Readers

one-vs-one-n-class.

Writers

(setf one-vs-one-n-class).

Slot: learners-vector
Readers

one-vs-one-learners-vector.

Writers

(setf one-vs-one-learners-vector).

Slot: learner-update
Readers

one-vs-one-learner-update.

Writers

(setf one-vs-one-learner-update).

Slot: learner-predict
Readers

one-vs-one-learner-predict.

Writers

(setf one-vs-one-learner-predict).

Structure: one-vs-rest
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

one-vs-rest-input-dimension.

Writers

(setf one-vs-rest-input-dimension).

Slot: n-class
Readers

one-vs-rest-n-class.

Writers

(setf one-vs-rest-n-class).

Slot: learners-vector
Readers

one-vs-rest-learners-vector.

Writers

(setf one-vs-rest-learners-vector).

Slot: learner-weight
Readers

one-vs-rest-learner-weight.

Writers

(setf one-vs-rest-learner-weight).

Slot: learner-bias
Readers

one-vs-rest-learner-bias.

Writers

(setf one-vs-rest-learner-bias).

Slot: learner-update
Readers

one-vs-rest-learner-update.

Writers

(setf one-vs-rest-learner-update).

Slot: learner-activate
Readers

one-vs-rest-learner-activate.

Writers

(setf one-vs-rest-learner-activate).

Structure: perceptron
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

perceptron-input-dimension.

Writers

(setf perceptron-input-dimension).

Slot: weight
Readers

perceptron-weight.

Writers

(setf perceptron-weight).

Slot: bias
Readers

perceptron-bias.

Writers

(setf perceptron-bias).

Slot: tmp-float
Readers

perceptron-tmp-float.

Writers

(setf perceptron-tmp-float).

Structure: rls
Package

cl-online-learning.

Source

rls.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

rls-input-dimension.

Writers

(setf rls-input-dimension).

Slot: weight
Readers

rls-weight.

Writers

(setf rls-weight).

Slot: bias
Readers

rls-bias.

Writers

(setf rls-bias).

Slot: gamma
Readers

rls-gamma.

Writers

(setf rls-gamma).

Slot: sigma
Readers

rls-sigma.

Writers

(setf rls-sigma).

Slot: sigma0
Readers

rls-sigma0.

Writers

(setf rls-sigma0).

Slot: tmp-vec1
Readers

rls-tmp-vec1.

Writers

(setf rls-tmp-vec1).

Slot: tmp-vec2
Readers

rls-tmp-vec2.

Writers

(setf rls-tmp-vec2).

Slot: tmp-float
Readers

rls-tmp-float.

Writers

(setf rls-tmp-float).

Structure: scw
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

scw-input-dimension.

Writers

(setf scw-input-dimension).

Slot: weight
Readers

scw-weight.

Writers

(setf scw-weight).

Slot: bias
Readers

scw-bias.

Writers

(setf scw-bias).

Slot: eta
Readers

scw-eta.

Writers

(setf scw-eta).

Slot: c
Readers

scw-c.

Writers

(setf scw-c).

Slot: phi
Readers

scw-phi.

Writers

(setf scw-phi).

Slot: psi
Readers

scw-psi.

Writers

(setf scw-psi).

Slot: zeta
Readers

scw-zeta.

Writers

(setf scw-zeta).

Slot: sigma
Readers

scw-sigma.

Writers

(setf scw-sigma).

Slot: sigma0
Readers

scw-sigma0.

Writers

(setf scw-sigma0).

Slot: tmp-vec1
Readers

scw-tmp-vec1.

Writers

(setf scw-tmp-vec1).

Slot: tmp-vec2
Readers

scw-tmp-vec2.

Writers

(setf scw-tmp-vec2).

Slot: tmp-float
Readers

scw-tmp-float.

Writers

(setf scw-tmp-float).

Structure: sparse-arow
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

sparse-arow-input-dimension.

Writers

(setf sparse-arow-input-dimension).

Slot: weight
Readers

sparse-arow-weight.

Writers

(setf sparse-arow-weight).

Slot: bias
Readers

sparse-arow-bias.

Writers

(setf sparse-arow-bias).

Slot: gamma
Readers

sparse-arow-gamma.

Writers

(setf sparse-arow-gamma).

Slot: sigma
Readers

sparse-arow-sigma.

Writers

(setf sparse-arow-sigma).

Slot: sigma0
Readers

sparse-arow-sigma0.

Writers

(setf sparse-arow-sigma0).

Slot: tmp-vec1
Readers

sparse-arow-tmp-vec1.

Writers

(setf sparse-arow-tmp-vec1).

Slot: tmp-vec2
Readers

sparse-arow-tmp-vec2.

Writers

(setf sparse-arow-tmp-vec2).

Slot: tmp-float
Readers

sparse-arow-tmp-float.

Writers

(setf sparse-arow-tmp-float).

Structure: sparse-lr+adam
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

sparse-lr+adam-input-dimension.

Writers

(setf sparse-lr+adam-input-dimension).

Slot: weight
Readers

sparse-lr+adam-weight.

Writers

(setf sparse-lr+adam-weight).

Slot: bias
Readers

sparse-lr+adam-bias.

Writers

(setf sparse-lr+adam-bias).

Slot: c
Readers

sparse-lr+adam-c.

Writers

(setf sparse-lr+adam-c).

Slot: alpha
Readers

sparse-lr+adam-alpha.

Writers

(setf sparse-lr+adam-alpha).

Slot: epsilon
Readers

sparse-lr+adam-epsilon.

Writers

(setf sparse-lr+adam-epsilon).

Slot: beta1
Readers

sparse-lr+adam-beta1.

Writers

(setf sparse-lr+adam-beta1).

Slot: beta2
Readers

sparse-lr+adam-beta2.

Writers

(setf sparse-lr+adam-beta2).

Slot: g
Readers

sparse-lr+adam-g.

Writers

(setf sparse-lr+adam-g).

Slot: m
Readers

sparse-lr+adam-m.

Writers

(setf sparse-lr+adam-m).

Slot: v
Readers

sparse-lr+adam-v.

Writers

(setf sparse-lr+adam-v).

Slot: m0
Readers

sparse-lr+adam-m0.

Writers

(setf sparse-lr+adam-m0).

Slot: v0
Readers

sparse-lr+adam-v0.

Writers

(setf sparse-lr+adam-v0).

Slot: beta1^t
Readers

sparse-lr+adam-beta1^t.

Writers

(setf sparse-lr+adam-beta1^t).

Slot: beta2^t
Readers

sparse-lr+adam-beta2^t.

Writers

(setf sparse-lr+adam-beta2^t).

Slot: tmp-vec
Readers

sparse-lr+adam-tmp-vec.

Writers

(setf sparse-lr+adam-tmp-vec).

Slot: tmp-float
Readers

sparse-lr+adam-tmp-float.

Writers

(setf sparse-lr+adam-tmp-float).

Structure: sparse-lr+sgd
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct slots
Slot: input-dimension
Readers

sparse-lr+sgd-input-dimension.

Writers

(setf sparse-lr+sgd-input-dimension).

Slot: weight
Readers

sparse-lr+sgd-weight.

Writers

(setf sparse-lr+sgd-weight).

Slot: bias
Readers

sparse-lr+sgd-bias.

Writers

(setf sparse-lr+sgd-bias).

Slot: c
Readers

sparse-lr+sgd-c.

Writers

(setf sparse-lr+sgd-c).

Slot: eta
Readers

sparse-lr+sgd-eta.

Writers

(setf sparse-lr+sgd-eta).

Slot: g
Readers

sparse-lr+sgd-g.

Writers

(setf sparse-lr+sgd-g).

Slot: tmp-vec
Readers

sparse-lr+sgd-tmp-vec.

Writers

(setf sparse-lr+sgd-tmp-vec).

Slot: tmp-float
Readers

sparse-lr+sgd-tmp-float.

Writers

(setf sparse-lr+sgd-tmp-float).

Structure: sparse-perceptron
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

sparse-perceptron-input-dimension.

Writers

(setf sparse-perceptron-input-dimension).

Slot: weight
Readers

sparse-perceptron-weight.

Writers

(setf sparse-perceptron-weight).

Slot: bias
Readers

sparse-perceptron-bias.

Writers

(setf sparse-perceptron-bias).

Slot: tmp-float
Readers

sparse-perceptron-tmp-float.

Writers

(setf sparse-perceptron-tmp-float).

Structure: sparse-rls
Package

cl-online-learning.

Source

rls.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

sparse-rls-input-dimension.

Writers

(setf sparse-rls-input-dimension).

Slot: weight
Readers

sparse-rls-weight.

Writers

(setf sparse-rls-weight).

Slot: bias
Readers

sparse-rls-bias.

Writers

(setf sparse-rls-bias).

Slot: gamma
Readers

sparse-rls-gamma.

Writers

(setf sparse-rls-gamma).

Slot: sigma
Readers

sparse-rls-sigma.

Writers

(setf sparse-rls-sigma).

Slot: sigma0
Readers

sparse-rls-sigma0.

Writers

(setf sparse-rls-sigma0).

Slot: tmp-vec1
Readers

sparse-rls-tmp-vec1.

Writers

(setf sparse-rls-tmp-vec1).

Slot: tmp-vec2
Readers

sparse-rls-tmp-vec2.

Writers

(setf sparse-rls-tmp-vec2).

Slot: tmp-float
Readers

sparse-rls-tmp-float.

Writers

(setf sparse-rls-tmp-float).

Structure: sparse-scw
Package

cl-online-learning.

Source

cl-online-learning.lisp.

Direct superclasses

structure-object.

Direct methods

print-object.

Direct slots
Slot: input-dimension
Readers

sparse-scw-input-dimension.

Writers

(setf sparse-scw-input-dimension).

Slot: weight
Readers

sparse-scw-weight.

Writers

(setf sparse-scw-weight).

Slot: bias
Readers

sparse-scw-bias.

Writers

(setf sparse-scw-bias).

Slot: eta
Readers

sparse-scw-eta.

Writers

(setf sparse-scw-eta).

Slot: c
Readers

sparse-scw-c.

Writers

(setf sparse-scw-c).

Slot: phi
Readers

sparse-scw-phi.

Writers

(setf sparse-scw-phi).

Slot: psi
Readers

sparse-scw-psi.

Writers

(setf sparse-scw-psi).

Slot: zeta
Readers

sparse-scw-zeta.

Writers

(setf sparse-scw-zeta).

Slot: sigma
Readers

sparse-scw-sigma.

Writers

(setf sparse-scw-sigma).

Slot: sigma0
Readers

sparse-scw-sigma0.

Writers

(setf sparse-scw-sigma0).

Slot: tmp-vec1
Readers

sparse-scw-tmp-vec1.

Writers

(setf sparse-scw-tmp-vec1).

Slot: tmp-vec2
Readers

sparse-scw-tmp-vec2.

Writers

(setf sparse-scw-tmp-vec2).

Slot: tmp-float
Readers

sparse-scw-tmp-float.

Writers

(setf sparse-scw-tmp-float).


Appendix A Indexes


A.1 Concepts


A.2 Functions

Jump to:   %   (  
A   C   D   F   G   I   L   M   N   O   P   R   S   T   V  
Index Entry  Section

%
%make-arow: Private ordinary functions
%make-lr+adam: Private ordinary functions
%make-lr+sgd: Private ordinary functions
%make-one-vs-one: Private ordinary functions
%make-one-vs-rest: Private ordinary functions
%make-perceptron: Private ordinary functions
%make-rls: Private ordinary functions
%make-scw: Private ordinary functions
%make-sparse-arow: Private ordinary functions
%make-sparse-lr+adam: Private ordinary functions
%make-sparse-lr+sgd: Private ordinary functions
%make-sparse-perceptron: Private ordinary functions
%make-sparse-rls: Private ordinary functions
%make-sparse-scw: Private ordinary functions
%make-sparse-vector: Private ordinary functions
%print-arow: Private ordinary functions
%print-lr+adam: Private ordinary functions
%print-one-vs-one: Private ordinary functions
%print-one-vs-rest: Private ordinary functions
%print-perceptron: Private ordinary functions
%print-rls: Private ordinary functions
%print-scw: Private ordinary functions
%print-sparse-arow: Private ordinary functions
%print-sparse-lr+adam: Private ordinary functions
%print-sparse-perceptron: Private ordinary functions
%print-sparse-rls: Private ordinary functions
%print-sparse-scw: Private ordinary functions

(
(setf argument-error-message): Private generic functions
(setf argument-error-message): Private generic functions
(setf arow-bias): Private ordinary functions
(setf arow-gamma): Private ordinary functions
(setf arow-input-dimension): Private ordinary functions
(setf arow-sigma): Private ordinary functions
(setf arow-sigma0): Private ordinary functions
(setf arow-tmp-float): Private ordinary functions
(setf arow-tmp-vec1): Private ordinary functions
(setf arow-tmp-vec2): Private ordinary functions
(setf arow-weight): Private ordinary functions
(setf lr+adam-alpha): Private ordinary functions
(setf lr+adam-beta1): Private ordinary functions
(setf lr+adam-beta1^t): Private ordinary functions
(setf lr+adam-beta2): Private ordinary functions
(setf lr+adam-beta2^t): Private ordinary functions
(setf lr+adam-bias): Private ordinary functions
(setf lr+adam-c): Private ordinary functions
(setf lr+adam-epsilon): Private ordinary functions
(setf lr+adam-g): Private ordinary functions
(setf lr+adam-input-dimension): Private ordinary functions
(setf lr+adam-m): Private ordinary functions
(setf lr+adam-m0): Private ordinary functions
(setf lr+adam-tmp-float): Private ordinary functions
(setf lr+adam-tmp-vec): Private ordinary functions
(setf lr+adam-v): Private ordinary functions
(setf lr+adam-v0): Private ordinary functions
(setf lr+adam-weight): Private ordinary functions
(setf lr+sgd-bias): Private ordinary functions
(setf lr+sgd-c): Private ordinary functions
(setf lr+sgd-eta): Private ordinary functions
(setf lr+sgd-g): Private ordinary functions
(setf lr+sgd-input-dimension): Private ordinary functions
(setf lr+sgd-tmp-float): Private ordinary functions
(setf lr+sgd-tmp-vec): Private ordinary functions
(setf lr+sgd-weight): Private ordinary functions
(setf one-vs-one-input-dimension): Private ordinary functions
(setf one-vs-one-learner-predict): Private ordinary functions
(setf one-vs-one-learner-update): Private ordinary functions
(setf one-vs-one-learners-vector): Private ordinary functions
(setf one-vs-one-n-class): Private ordinary functions
(setf one-vs-rest-input-dimension): Private ordinary functions
(setf one-vs-rest-learner-activate): Private ordinary functions
(setf one-vs-rest-learner-bias): Private ordinary functions
(setf one-vs-rest-learner-update): Private ordinary functions
(setf one-vs-rest-learner-weight): Private ordinary functions
(setf one-vs-rest-learners-vector): Private ordinary functions
(setf one-vs-rest-n-class): Private ordinary functions
(setf perceptron-bias): Private ordinary functions
(setf perceptron-input-dimension): Private ordinary functions
(setf perceptron-tmp-float): Private ordinary functions
(setf perceptron-weight): Private ordinary functions
(setf rls-bias): Private ordinary functions
(setf rls-gamma): Private ordinary functions
(setf rls-input-dimension): Private ordinary functions
(setf rls-sigma): Private ordinary functions
(setf rls-sigma0): Private ordinary functions
(setf rls-tmp-float): Private ordinary functions
(setf rls-tmp-vec1): Private ordinary functions
(setf rls-tmp-vec2): Private ordinary functions
(setf rls-weight): Private ordinary functions
(setf scw-bias): Private ordinary functions
(setf scw-c): Private ordinary functions
(setf scw-eta): Private ordinary functions
(setf scw-input-dimension): Private ordinary functions
(setf scw-phi): Private ordinary functions
(setf scw-psi): Private ordinary functions
(setf scw-sigma): Private ordinary functions
(setf scw-sigma0): Private ordinary functions
(setf scw-tmp-float): Private ordinary functions
(setf scw-tmp-vec1): Private ordinary functions
(setf scw-tmp-vec2): Private ordinary functions
(setf scw-weight): Private ordinary functions
(setf scw-zeta): Private ordinary functions
(setf sparse-arow-bias): Private ordinary functions
(setf sparse-arow-gamma): Private ordinary functions
(setf sparse-arow-input-dimension): Private ordinary functions
(setf sparse-arow-sigma): Private ordinary functions
(setf sparse-arow-sigma0): Private ordinary functions
(setf sparse-arow-tmp-float): Private ordinary functions
(setf sparse-arow-tmp-vec1): Private ordinary functions
(setf sparse-arow-tmp-vec2): Private ordinary functions
(setf sparse-arow-weight): Private ordinary functions
(setf sparse-lr+adam-alpha): Private ordinary functions
(setf sparse-lr+adam-beta1): Private ordinary functions
(setf sparse-lr+adam-beta1^t): Private ordinary functions
(setf sparse-lr+adam-beta2): Private ordinary functions
(setf sparse-lr+adam-beta2^t): Private ordinary functions
(setf sparse-lr+adam-bias): Private ordinary functions
(setf sparse-lr+adam-c): Private ordinary functions
(setf sparse-lr+adam-epsilon): Private ordinary functions
(setf sparse-lr+adam-g): Private ordinary functions
(setf sparse-lr+adam-input-dimension): Private ordinary functions
(setf sparse-lr+adam-m): Private ordinary functions
(setf sparse-lr+adam-m0): Private ordinary functions
(setf sparse-lr+adam-tmp-float): Private ordinary functions
(setf sparse-lr+adam-tmp-vec): Private ordinary functions
(setf sparse-lr+adam-v): Private ordinary functions
(setf sparse-lr+adam-v0): Private ordinary functions
(setf sparse-lr+adam-weight): Private ordinary functions
(setf sparse-lr+sgd-bias): Private ordinary functions
(setf sparse-lr+sgd-c): Private ordinary functions
(setf sparse-lr+sgd-eta): Private ordinary functions
(setf sparse-lr+sgd-g): Private ordinary functions
(setf sparse-lr+sgd-input-dimension): Private ordinary functions
(setf sparse-lr+sgd-tmp-float): Private ordinary functions
(setf sparse-lr+sgd-tmp-vec): Private ordinary functions
(setf sparse-lr+sgd-weight): Private ordinary functions
(setf sparse-perceptron-bias): Private ordinary functions
(setf sparse-perceptron-input-dimension): Private ordinary functions
(setf sparse-perceptron-tmp-float): Private ordinary functions
(setf sparse-perceptron-weight): Private ordinary functions
(setf sparse-rls-bias): Private ordinary functions
(setf sparse-rls-gamma): Private ordinary functions
(setf sparse-rls-input-dimension): Private ordinary functions
(setf sparse-rls-sigma): Private ordinary functions
(setf sparse-rls-sigma0): Private ordinary functions
(setf sparse-rls-tmp-float): Private ordinary functions
(setf sparse-rls-tmp-vec1): Private ordinary functions
(setf sparse-rls-tmp-vec2): Private ordinary functions
(setf sparse-rls-weight): Private ordinary functions
(setf sparse-scw-bias): Private ordinary functions
(setf sparse-scw-c): Private ordinary functions
(setf sparse-scw-eta): Private ordinary functions
(setf sparse-scw-input-dimension): Private ordinary functions
(setf sparse-scw-phi): Private ordinary functions
(setf sparse-scw-psi): Private ordinary functions
(setf sparse-scw-sigma): Private ordinary functions
(setf sparse-scw-sigma0): Private ordinary functions
(setf sparse-scw-tmp-float): Private ordinary functions
(setf sparse-scw-tmp-vec1): Private ordinary functions
(setf sparse-scw-tmp-vec2): Private ordinary functions
(setf sparse-scw-weight): Private ordinary functions
(setf sparse-scw-zeta): Private ordinary functions
(setf sparse-vector-index-vector): Public ordinary functions
(setf sparse-vector-length): Public ordinary functions
(setf sparse-vector-value-vector): Public ordinary functions

A
arg-list->lambda-arg: Private ordinary functions
argument-error-message: Private generic functions
argument-error-message: Private generic functions
arow-bias: Private ordinary functions
arow-gamma: Private ordinary functions
arow-input-dimension: Private ordinary functions
arow-p: Private ordinary functions
arow-predict: Public ordinary functions
arow-sigma: Private ordinary functions
arow-sigma0: Private ordinary functions
arow-test: Public ordinary functions
arow-tmp-float: Private ordinary functions
arow-tmp-vec1: Private ordinary functions
arow-tmp-vec2: Private ordinary functions
arow-train: Public ordinary functions
arow-update: Public ordinary functions
arow-weight: Private ordinary functions

C
catstr: Private macros
class-min/max: Public ordinary functions
copy-arow: Private ordinary functions
copy-lr+adam: Private ordinary functions
copy-lr+sgd: Private ordinary functions
copy-one-vs-one: Private ordinary functions
copy-one-vs-rest: Private ordinary functions
copy-perceptron: Private ordinary functions
copy-rls: Private ordinary functions
copy-scw: Private ordinary functions
copy-sparse-arow: Private ordinary functions
copy-sparse-lr+adam: Private ordinary functions
copy-sparse-lr+sgd: Private ordinary functions
copy-sparse-perceptron: Private ordinary functions
copy-sparse-rls: Private ordinary functions
copy-sparse-scw: Private ordinary functions
copy-sparse-vector: Private ordinary functions

D
define-learner: Private macros
define-multi-class-learner-train/test-functions: Private macros
define-regression-learner: Private macros
defmain: Public macros
dim-of: Public ordinary functions
doseq: Private macros
dosvec: Public macros
dot: Public ordinary functions
dot!: Public ordinary functions
dovec: Public macros
dps-v*: Public ordinary functions
dps-v+: Public ordinary functions
dps-v-: Public ordinary functions
ds-dot: Public ordinary functions
ds-dot!: Public ordinary functions
ds-v*: Public ordinary functions
ds-v+: Public ordinary functions
ds-v-: Public ordinary functions
ds-v/: Public ordinary functions
ds2s-v*: Public ordinary functions

F
f: Private ordinary functions
f!: Private ordinary functions
flatten: Private ordinary functions
Function, %make-arow: Private ordinary functions
Function, %make-lr+adam: Private ordinary functions
Function, %make-lr+sgd: Private ordinary functions
Function, %make-one-vs-one: Private ordinary functions
Function, %make-one-vs-rest: Private ordinary functions
Function, %make-perceptron: Private ordinary functions
Function, %make-rls: Private ordinary functions
Function, %make-scw: Private ordinary functions
Function, %make-sparse-arow: Private ordinary functions
Function, %make-sparse-lr+adam: Private ordinary functions
Function, %make-sparse-lr+sgd: Private ordinary functions
Function, %make-sparse-perceptron: Private ordinary functions
Function, %make-sparse-rls: Private ordinary functions
Function, %make-sparse-scw: Private ordinary functions
Function, %make-sparse-vector: Private ordinary functions
Function, %print-arow: Private ordinary functions
Function, %print-lr+adam: Private ordinary functions
Function, %print-one-vs-one: Private ordinary functions
Function, %print-one-vs-rest: Private ordinary functions
Function, %print-perceptron: Private ordinary functions
Function, %print-rls: Private ordinary functions
Function, %print-scw: Private ordinary functions
Function, %print-sparse-arow: Private ordinary functions
Function, %print-sparse-lr+adam: Private ordinary functions
Function, %print-sparse-perceptron: Private ordinary functions
Function, %print-sparse-rls: Private ordinary functions
Function, %print-sparse-scw: Private ordinary functions
Function, (setf arow-bias): Private ordinary functions
Function, (setf arow-gamma): Private ordinary functions
Function, (setf arow-input-dimension): Private ordinary functions
Function, (setf arow-sigma): Private ordinary functions
Function, (setf arow-sigma0): Private ordinary functions
Function, (setf arow-tmp-float): Private ordinary functions
Function, (setf arow-tmp-vec1): Private ordinary functions
Function, (setf arow-tmp-vec2): Private ordinary functions
Function, (setf arow-weight): Private ordinary functions
Function, (setf lr+adam-alpha): Private ordinary functions
Function, (setf lr+adam-beta1): Private ordinary functions
Function, (setf lr+adam-beta1^t): Private ordinary functions
Function, (setf lr+adam-beta2): Private ordinary functions
Function, (setf lr+adam-beta2^t): Private ordinary functions
Function, (setf lr+adam-bias): Private ordinary functions
Function, (setf lr+adam-c): Private ordinary functions
Function, (setf lr+adam-epsilon): Private ordinary functions
Function, (setf lr+adam-g): Private ordinary functions
Function, (setf lr+adam-input-dimension): Private ordinary functions
Function, (setf lr+adam-m): Private ordinary functions
Function, (setf lr+adam-m0): Private ordinary functions
Function, (setf lr+adam-tmp-float): Private ordinary functions
Function, (setf lr+adam-tmp-vec): Private ordinary functions
Function, (setf lr+adam-v): Private ordinary functions
Function, (setf lr+adam-v0): Private ordinary functions
Function, (setf lr+adam-weight): Private ordinary functions
Function, (setf lr+sgd-bias): Private ordinary functions
Function, (setf lr+sgd-c): Private ordinary functions
Function, (setf lr+sgd-eta): Private ordinary functions
Function, (setf lr+sgd-g): Private ordinary functions
Function, (setf lr+sgd-input-dimension): Private ordinary functions
Function, (setf lr+sgd-tmp-float): Private ordinary functions
Function, (setf lr+sgd-tmp-vec): Private ordinary functions
Function, (setf lr+sgd-weight): Private ordinary functions
Function, (setf one-vs-one-input-dimension): Private ordinary functions
Function, (setf one-vs-one-learner-predict): Private ordinary functions
Function, (setf one-vs-one-learner-update): Private ordinary functions
Function, (setf one-vs-one-learners-vector): Private ordinary functions
Function, (setf one-vs-one-n-class): Private ordinary functions
Function, (setf one-vs-rest-input-dimension): Private ordinary functions
Function, (setf one-vs-rest-learner-activate): Private ordinary functions
Function, (setf one-vs-rest-learner-bias): Private ordinary functions
Function, (setf one-vs-rest-learner-update): Private ordinary functions
Function, (setf one-vs-rest-learner-weight): Private ordinary functions
Function, (setf one-vs-rest-learners-vector): Private ordinary functions
Function, (setf one-vs-rest-n-class): Private ordinary functions
Function, (setf perceptron-bias): Private ordinary functions
Function, (setf perceptron-input-dimension): Private ordinary functions
Function, (setf perceptron-tmp-float): Private ordinary functions
Function, (setf perceptron-weight): Private ordinary functions
Function, (setf rls-bias): Private ordinary functions
Function, (setf rls-gamma): Private ordinary functions
Function, (setf rls-input-dimension): Private ordinary functions
Function, (setf rls-sigma): Private ordinary functions
Function, (setf rls-sigma0): Private ordinary functions
Function, (setf rls-tmp-float): Private ordinary functions
Function, (setf rls-tmp-vec1): Private ordinary functions
Function, (setf rls-tmp-vec2): Private ordinary functions
Function, (setf rls-weight): Private ordinary functions
Function, (setf scw-bias): Private ordinary functions
Function, (setf scw-c): Private ordinary functions
Function, (setf scw-eta): Private ordinary functions
Function, (setf scw-input-dimension): Private ordinary functions
Function, (setf scw-phi): Private ordinary functions
Function, (setf scw-psi): Private ordinary functions
Function, (setf scw-sigma): Private ordinary functions
Function, (setf scw-sigma0): Private ordinary functions
Function, (setf scw-tmp-float): Private ordinary functions
Function, (setf scw-tmp-vec1): Private ordinary functions
Function, (setf scw-tmp-vec2): Private ordinary functions
Function, (setf scw-weight): Private ordinary functions
Function, (setf scw-zeta): Private ordinary functions
Function, (setf sparse-arow-bias): Private ordinary functions
Function, (setf sparse-arow-gamma): Private ordinary functions
Function, (setf sparse-arow-input-dimension): Private ordinary functions
Function, (setf sparse-arow-sigma): Private ordinary functions
Function, (setf sparse-arow-sigma0): Private ordinary functions
Function, (setf sparse-arow-tmp-float): Private ordinary functions
Function, (setf sparse-arow-tmp-vec1): Private ordinary functions
Function, (setf sparse-arow-tmp-vec2): Private ordinary functions
Function, (setf sparse-arow-weight): Private ordinary functions
Function, (setf sparse-lr+adam-alpha): Private ordinary functions
Function, (setf sparse-lr+adam-beta1): Private ordinary functions
Function, (setf sparse-lr+adam-beta1^t): Private ordinary functions
Function, (setf sparse-lr+adam-beta2): Private ordinary functions
Function, (setf sparse-lr+adam-beta2^t): Private ordinary functions
Function, (setf sparse-lr+adam-bias): Private ordinary functions
Function, (setf sparse-lr+adam-c): Private ordinary functions
Function, (setf sparse-lr+adam-epsilon): Private ordinary functions
Function, (setf sparse-lr+adam-g): Private ordinary functions
Function, (setf sparse-lr+adam-input-dimension): Private ordinary functions
Function, (setf sparse-lr+adam-m): Private ordinary functions
Function, (setf sparse-lr+adam-m0): Private ordinary functions
Function, (setf sparse-lr+adam-tmp-float): Private ordinary functions
Function, (setf sparse-lr+adam-tmp-vec): Private ordinary functions
Function, (setf sparse-lr+adam-v): Private ordinary functions
Function, (setf sparse-lr+adam-v0): Private ordinary functions
Function, (setf sparse-lr+adam-weight): Private ordinary functions
Function, (setf sparse-lr+sgd-bias): Private ordinary functions
Function, (setf sparse-lr+sgd-c): Private ordinary functions
Function, (setf sparse-lr+sgd-eta): Private ordinary functions
Function, (setf sparse-lr+sgd-g): Private ordinary functions
Function, (setf sparse-lr+sgd-input-dimension): Private ordinary functions
Function, (setf sparse-lr+sgd-tmp-float): Private ordinary functions
Function, (setf sparse-lr+sgd-tmp-vec): Private ordinary functions
Function, (setf sparse-lr+sgd-weight): Private ordinary functions
Function, (setf sparse-perceptron-bias): Private ordinary functions
Function, (setf sparse-perceptron-input-dimension): Private ordinary functions
Function, (setf sparse-perceptron-tmp-float): Private ordinary functions
Function, (setf sparse-perceptron-weight): Private ordinary functions
Function, (setf sparse-rls-bias): Private ordinary functions
Function, (setf sparse-rls-gamma): Private ordinary functions
Function, (setf sparse-rls-input-dimension): Private ordinary functions
Function, (setf sparse-rls-sigma): Private ordinary functions
Function, (setf sparse-rls-sigma0): Private ordinary functions
Function, (setf sparse-rls-tmp-float): Private ordinary functions
Function, (setf sparse-rls-tmp-vec1): Private ordinary functions
Function, (setf sparse-rls-tmp-vec2): Private ordinary functions
Function, (setf sparse-rls-weight): Private ordinary functions
Function, (setf sparse-scw-bias): Private ordinary functions
Function, (setf sparse-scw-c): Private ordinary functions
Function, (setf sparse-scw-eta): Private ordinary functions
Function, (setf sparse-scw-input-dimension): Private ordinary functions
Function, (setf sparse-scw-phi): Private ordinary functions
Function, (setf sparse-scw-psi): Private ordinary functions
Function, (setf sparse-scw-sigma): Private ordinary functions
Function, (setf sparse-scw-sigma0): Private ordinary functions
Function, (setf sparse-scw-tmp-float): Private ordinary functions
Function, (setf sparse-scw-tmp-vec1): Private ordinary functions
Function, (setf sparse-scw-tmp-vec2): Private ordinary functions
Function, (setf sparse-scw-weight): Private ordinary functions
Function, (setf sparse-scw-zeta): Private ordinary functions
Function, (setf sparse-vector-index-vector): Public ordinary functions
Function, (setf sparse-vector-length): Public ordinary functions
Function, (setf sparse-vector-value-vector): Public ordinary functions
Function, arg-list->lambda-arg: Private ordinary functions
Function, arow-bias: Private ordinary functions
Function, arow-gamma: Private ordinary functions
Function, arow-input-dimension: Private ordinary functions
Function, arow-p: Private ordinary functions
Function, arow-predict: Public ordinary functions
Function, arow-sigma: Private ordinary functions
Function, arow-sigma0: Private ordinary functions
Function, arow-test: Public ordinary functions
Function, arow-tmp-float: Private ordinary functions
Function, arow-tmp-vec1: Private ordinary functions
Function, arow-tmp-vec2: Private ordinary functions
Function, arow-train: Public ordinary functions
Function, arow-update: Public ordinary functions
Function, arow-weight: Private ordinary functions
Function, class-min/max: Public ordinary functions
Function, copy-arow: Private ordinary functions
Function, copy-lr+adam: Private ordinary functions
Function, copy-lr+sgd: Private ordinary functions
Function, copy-one-vs-one: Private ordinary functions
Function, copy-one-vs-rest: Private ordinary functions
Function, copy-perceptron: Private ordinary functions
Function, copy-rls: Private ordinary functions
Function, copy-scw: Private ordinary functions
Function, copy-sparse-arow: Private ordinary functions
Function, copy-sparse-lr+adam: Private ordinary functions
Function, copy-sparse-lr+sgd: Private ordinary functions
Function, copy-sparse-perceptron: Private ordinary functions
Function, copy-sparse-rls: Private ordinary functions
Function, copy-sparse-scw: Private ordinary functions
Function, copy-sparse-vector: Private ordinary functions
Function, dim-of: Public ordinary functions
Function, dot: Public ordinary functions
Function, dot!: Public ordinary functions
Function, dps-v*: Public ordinary functions
Function, dps-v+: Public ordinary functions
Function, dps-v-: Public ordinary functions
Function, ds-dot: Public ordinary functions
Function, ds-dot!: Public ordinary functions
Function, ds-v*: Public ordinary functions
Function, ds-v+: Public ordinary functions
Function, ds-v-: Public ordinary functions
Function, ds-v/: Public ordinary functions
Function, ds2s-v*: Public ordinary functions
Function, f: Private ordinary functions
Function, f!: Private ordinary functions
Function, flatten: Private ordinary functions
Function, group-arg-list: Private ordinary functions
Function, index-of-learner: Private ordinary functions
Function, inverse-erf: Private ordinary functions
Function, logistic-regression-gradient!: Private ordinary functions
Function, logistic-regression-gradient-sparse!: Private ordinary functions
Function, lr+adam-alpha: Private ordinary functions
Function, lr+adam-beta1: Private ordinary functions
Function, lr+adam-beta1^t: Private ordinary functions
Function, lr+adam-beta2: Private ordinary functions
Function, lr+adam-beta2^t: Private ordinary functions
Function, lr+adam-bias: Private ordinary functions
Function, lr+adam-c: Private ordinary functions
Function, lr+adam-epsilon: Private ordinary functions
Function, lr+adam-g: Private ordinary functions
Function, lr+adam-input-dimension: Private ordinary functions
Function, lr+adam-m: Private ordinary functions
Function, lr+adam-m0: Private ordinary functions
Function, lr+adam-p: Private ordinary functions
Function, lr+adam-predict: Public ordinary functions
Function, lr+adam-test: Public ordinary functions
Function, lr+adam-tmp-float: Private ordinary functions
Function, lr+adam-tmp-vec: Private ordinary functions
Function, lr+adam-train: Public ordinary functions
Function, lr+adam-update: Public ordinary functions
Function, lr+adam-v: Private ordinary functions
Function, lr+adam-v0: Private ordinary functions
Function, lr+adam-weight: Private ordinary functions
Function, lr+sgd-bias: Private ordinary functions
Function, lr+sgd-c: Private ordinary functions
Function, lr+sgd-eta: Private ordinary functions
Function, lr+sgd-g: Private ordinary functions
Function, lr+sgd-input-dimension: Private ordinary functions
Function, lr+sgd-p: Private ordinary functions
Function, lr+sgd-predict: Public ordinary functions
Function, lr+sgd-test: Public ordinary functions
Function, lr+sgd-tmp-float: Private ordinary functions
Function, lr+sgd-tmp-vec: Private ordinary functions
Function, lr+sgd-train: Public ordinary functions
Function, lr+sgd-update: Public ordinary functions
Function, lr+sgd-weight: Private ordinary functions
Function, make-arow: Public ordinary functions
Function, make-empty-sparse-vector: Public ordinary functions
Function, make-lr+adam: Public ordinary functions
Function, make-lr+sgd: Public ordinary functions
Function, make-one-vs-one: Public ordinary functions
Function, make-one-vs-rest: Public ordinary functions
Function, make-perceptron: Public ordinary functions
Function, make-rls: Public ordinary functions
Function, make-scw: Public ordinary functions
Function, make-sparse-arow: Public ordinary functions
Function, make-sparse-lr+adam: Public ordinary functions
Function, make-sparse-lr+sgd: Public ordinary functions
Function, make-sparse-perceptron: Public ordinary functions
Function, make-sparse-rls: Public ordinary functions
Function, make-sparse-scw: Public ordinary functions
Function, make-sparse-vector: Public ordinary functions
Function, make-vec: Public ordinary functions
Function, mean-vector: Private ordinary functions
Function, n-class-of: Public ordinary functions
Function, one-vs-one-clear-functions-for-store: Private ordinary functions
Function, one-vs-one-input-dimension: Private ordinary functions
Function, one-vs-one-learner-predict: Private ordinary functions
Function, one-vs-one-learner-update: Private ordinary functions
Function, one-vs-one-learners-vector: Private ordinary functions
Function, one-vs-one-n-class: Private ordinary functions
Function, one-vs-one-p: Private ordinary functions
Function, one-vs-one-predict: Public ordinary functions
Function, one-vs-one-restore-functions: Private ordinary functions
Function, one-vs-one-test: Public ordinary functions
Function, one-vs-one-train: Public ordinary functions
Function, one-vs-one-update: Public ordinary functions
Function, one-vs-rest-clear-functions-for-store: Private ordinary functions
Function, one-vs-rest-input-dimension: Private ordinary functions
Function, one-vs-rest-learner-activate: Private ordinary functions
Function, one-vs-rest-learner-bias: Private ordinary functions
Function, one-vs-rest-learner-update: Private ordinary functions
Function, one-vs-rest-learner-weight: Private ordinary functions
Function, one-vs-rest-learners-vector: Private ordinary functions
Function, one-vs-rest-n-class: Private ordinary functions
Function, one-vs-rest-p: Private ordinary functions
Function, one-vs-rest-predict: Public ordinary functions
Function, one-vs-rest-restore-functions: Private ordinary functions
Function, one-vs-rest-test: Public ordinary functions
Function, one-vs-rest-train: Public ordinary functions
Function, one-vs-rest-update: Public ordinary functions
Function, perceptron-bias: Private ordinary functions
Function, perceptron-input-dimension: Private ordinary functions
Function, perceptron-p: Private ordinary functions
Function, perceptron-predict: Public ordinary functions
Function, perceptron-test: Public ordinary functions
Function, perceptron-tmp-float: Private ordinary functions
Function, perceptron-train: Public ordinary functions
Function, perceptron-update: Public ordinary functions
Function, perceptron-weight: Private ordinary functions
Function, probit: Private ordinary functions
Function, ps-v*n: Public ordinary functions
Function, read-data: Public ordinary functions
Function, read-datum: Private ordinary functions
Function, read-datum-sparse: Private ordinary functions
Function, restore: Public ordinary functions
Function, rls-bias: Private ordinary functions
Function, rls-gamma: Private ordinary functions
Function, rls-input-dimension: Private ordinary functions
Function, rls-p: Private ordinary functions
Function, rls-predict: Public ordinary functions
Function, rls-sigma: Private ordinary functions
Function, rls-sigma0: Private ordinary functions
Function, rls-test: Public ordinary functions
Function, rls-tmp-float: Private ordinary functions
Function, rls-tmp-vec1: Private ordinary functions
Function, rls-tmp-vec2: Private ordinary functions
Function, rls-train: Public ordinary functions
Function, rls-update: Public ordinary functions
Function, rls-weight: Private ordinary functions
Function, s-v*n: Public ordinary functions
Function, sanity-check: Private ordinary functions
Function, save: Public ordinary functions
Function, scw-bias: Private ordinary functions
Function, scw-c: Private ordinary functions
Function, scw-eta: Private ordinary functions
Function, scw-input-dimension: Private ordinary functions
Function, scw-p: Private ordinary functions
Function, scw-phi: Private ordinary functions
Function, scw-predict: Public ordinary functions
Function, scw-psi: Private ordinary functions
Function, scw-sigma: Private ordinary functions
Function, scw-sigma0: Private ordinary functions
Function, scw-test: Public ordinary functions
Function, scw-tmp-float: Private ordinary functions
Function, scw-tmp-vec1: Private ordinary functions
Function, scw-tmp-vec2: Private ordinary functions
Function, scw-train: Public ordinary functions
Function, scw-update: Public ordinary functions
Function, scw-weight: Private ordinary functions
Function, scw-zeta: Private ordinary functions
Function, sf: Private ordinary functions
Function, sf!: Private ordinary functions
Function, shuffle-vector: Public ordinary functions
Function, sign: Private ordinary functions
Function, sparse-arow-bias: Private ordinary functions
Function, sparse-arow-gamma: Private ordinary functions
Function, sparse-arow-input-dimension: Private ordinary functions
Function, sparse-arow-p: Private ordinary functions
Function, sparse-arow-predict: Public ordinary functions
Function, sparse-arow-sigma: Private ordinary functions
Function, sparse-arow-sigma0: Private ordinary functions
Function, sparse-arow-test: Public ordinary functions
Function, sparse-arow-tmp-float: Private ordinary functions
Function, sparse-arow-tmp-vec1: Private ordinary functions
Function, sparse-arow-tmp-vec2: Private ordinary functions
Function, sparse-arow-train: Public ordinary functions
Function, sparse-arow-update: Public ordinary functions
Function, sparse-arow-weight: Private ordinary functions
Function, sparse-learner?: Public ordinary functions
Function, sparse-lr+adam-alpha: Private ordinary functions
Function, sparse-lr+adam-beta1: Private ordinary functions
Function, sparse-lr+adam-beta1^t: Private ordinary functions
Function, sparse-lr+adam-beta2: Private ordinary functions
Function, sparse-lr+adam-beta2^t: Private ordinary functions
Function, sparse-lr+adam-bias: Private ordinary functions
Function, sparse-lr+adam-c: Private ordinary functions
Function, sparse-lr+adam-epsilon: Private ordinary functions
Function, sparse-lr+adam-g: Private ordinary functions
Function, sparse-lr+adam-input-dimension: Private ordinary functions
Function, sparse-lr+adam-m: Private ordinary functions
Function, sparse-lr+adam-m0: Private ordinary functions
Function, sparse-lr+adam-p: Private ordinary functions
Function, sparse-lr+adam-predict: Public ordinary functions
Function, sparse-lr+adam-test: Public ordinary functions
Function, sparse-lr+adam-tmp-float: Private ordinary functions
Function, sparse-lr+adam-tmp-vec: Private ordinary functions
Function, sparse-lr+adam-train: Public ordinary functions
Function, sparse-lr+adam-update: Public ordinary functions
Function, sparse-lr+adam-v: Private ordinary functions
Function, sparse-lr+adam-v0: Private ordinary functions
Function, sparse-lr+adam-weight: Private ordinary functions
Function, sparse-lr+sgd-bias: Private ordinary functions
Function, sparse-lr+sgd-c: Private ordinary functions
Function, sparse-lr+sgd-eta: Private ordinary functions
Function, sparse-lr+sgd-g: Private ordinary functions
Function, sparse-lr+sgd-input-dimension: Private ordinary functions
Function, sparse-lr+sgd-p: Private ordinary functions
Function, sparse-lr+sgd-predict: Public ordinary functions
Function, sparse-lr+sgd-test: Public ordinary functions
Function, sparse-lr+sgd-tmp-float: Private ordinary functions
Function, sparse-lr+sgd-tmp-vec: Private ordinary functions
Function, sparse-lr+sgd-train: Public ordinary functions
Function, sparse-lr+sgd-update: Public ordinary functions
Function, sparse-lr+sgd-weight: Private ordinary functions
Function, sparse-perceptron-bias: Private ordinary functions
Function, sparse-perceptron-input-dimension: Private ordinary functions
Function, sparse-perceptron-p: Private ordinary functions
Function, sparse-perceptron-predict: Public ordinary functions
Function, sparse-perceptron-test: Public ordinary functions
Function, sparse-perceptron-tmp-float: Private ordinary functions
Function, sparse-perceptron-train: Public ordinary functions
Function, sparse-perceptron-update: Public ordinary functions
Function, sparse-perceptron-weight: Private ordinary functions
Function, sparse-rls-bias: Private ordinary functions
Function, sparse-rls-gamma: Private ordinary functions
Function, sparse-rls-input-dimension: Private ordinary functions
Function, sparse-rls-p: Private ordinary functions
Function, sparse-rls-predict: Public ordinary functions
Function, sparse-rls-sigma: Private ordinary functions
Function, sparse-rls-sigma0: Private ordinary functions
Function, sparse-rls-test: Public ordinary functions
Function, sparse-rls-tmp-float: Private ordinary functions
Function, sparse-rls-tmp-vec1: Private ordinary functions
Function, sparse-rls-tmp-vec2: Private ordinary functions
Function, sparse-rls-train: Public ordinary functions
Function, sparse-rls-update: Public ordinary functions
Function, sparse-rls-weight: Private ordinary functions
Function, sparse-scw-bias: Private ordinary functions
Function, sparse-scw-c: Private ordinary functions
Function, sparse-scw-eta: Private ordinary functions
Function, sparse-scw-input-dimension: Private ordinary functions
Function, sparse-scw-p: Private ordinary functions
Function, sparse-scw-phi: Private ordinary functions
Function, sparse-scw-predict: Public ordinary functions
Function, sparse-scw-psi: Private ordinary functions
Function, sparse-scw-sigma: Private ordinary functions
Function, sparse-scw-sigma0: Private ordinary functions
Function, sparse-scw-test: Public ordinary functions
Function, sparse-scw-tmp-float: Private ordinary functions
Function, sparse-scw-tmp-vec1: Private ordinary functions
Function, sparse-scw-tmp-vec2: Private ordinary functions
Function, sparse-scw-train: Public ordinary functions
Function, sparse-scw-update: Public ordinary functions
Function, sparse-scw-weight: Private ordinary functions
Function, sparse-scw-zeta: Private ordinary functions
Function, sparse-symbol?: Private ordinary functions
Function, sparse-vector-index-vector: Public ordinary functions
Function, sparse-vector-length: Public ordinary functions
Function, sparse-vector-p: Private ordinary functions
Function, sparse-vector-value-vector: Public ordinary functions
Function, split-lambda-list: Private ordinary functions
Function, sps-v*n: Public ordinary functions
Function, standard-deviation-vector: Private ordinary functions
Function, sum-permutation: Private ordinary functions
Function, test: Public ordinary functions
Function, to-float: Public ordinary functions
Function, to-int: Public ordinary functions
Function, train: Public ordinary functions
Function, v*: Public ordinary functions
Function, v*n: Public ordinary functions
Function, v+: Public ordinary functions
Function, v+n: Public ordinary functions
Function, v-: Public ordinary functions
Function, v-sqrt: Public ordinary functions
Function, v/: Public ordinary functions
function-by-name: Private macros

G
Generic Function, (setf argument-error-message): Private generic functions
Generic Function, argument-error-message: Private generic functions
group-arg-list: Private ordinary functions

I
index-of-learner: Private ordinary functions
inverse-erf: Private ordinary functions

L
logistic-regression-gradient!: Private ordinary functions
logistic-regression-gradient-sparse!: Private ordinary functions
lr+adam-alpha: Private ordinary functions
lr+adam-beta1: Private ordinary functions
lr+adam-beta1^t: Private ordinary functions
lr+adam-beta2: Private ordinary functions
lr+adam-beta2^t: Private ordinary functions
lr+adam-bias: Private ordinary functions
lr+adam-c: Private ordinary functions
lr+adam-epsilon: Private ordinary functions
lr+adam-g: Private ordinary functions
lr+adam-input-dimension: Private ordinary functions
lr+adam-m: Private ordinary functions
lr+adam-m0: Private ordinary functions
lr+adam-p: Private ordinary functions
lr+adam-predict: Public ordinary functions
lr+adam-test: Public ordinary functions
lr+adam-tmp-float: Private ordinary functions
lr+adam-tmp-vec: Private ordinary functions
lr+adam-train: Public ordinary functions
lr+adam-update: Public ordinary functions
lr+adam-v: Private ordinary functions
lr+adam-v0: Private ordinary functions
lr+adam-weight: Private ordinary functions
lr+sgd-bias: Private ordinary functions
lr+sgd-c: Private ordinary functions
lr+sgd-eta: Private ordinary functions
lr+sgd-g: Private ordinary functions
lr+sgd-input-dimension: Private ordinary functions
lr+sgd-p: Private ordinary functions
lr+sgd-predict: Public ordinary functions
lr+sgd-test: Public ordinary functions
lr+sgd-tmp-float: Private ordinary functions
lr+sgd-tmp-vec: Private ordinary functions
lr+sgd-train: Public ordinary functions
lr+sgd-update: Public ordinary functions
lr+sgd-weight: Private ordinary functions

M
Macro, catstr: Private macros
Macro, define-learner: Private macros
Macro, define-multi-class-learner-train/test-functions: Private macros
Macro, define-regression-learner: Private macros
Macro, defmain: Public macros
Macro, doseq: Private macros
Macro, dosvec: Public macros
Macro, dovec: Public macros
Macro, function-by-name: Private macros
Macro, sigmoid: Private macros
make-arow: Public ordinary functions
make-empty-sparse-vector: Public ordinary functions
make-lr+adam: Public ordinary functions
make-lr+sgd: Public ordinary functions
make-one-vs-one: Public ordinary functions
make-one-vs-rest: Public ordinary functions
make-perceptron: Public ordinary functions
make-rls: Public ordinary functions
make-scw: Public ordinary functions
make-sparse-arow: Public ordinary functions
make-sparse-lr+adam: Public ordinary functions
make-sparse-lr+sgd: Public ordinary functions
make-sparse-perceptron: Public ordinary functions
make-sparse-rls: Public ordinary functions
make-sparse-scw: Public ordinary functions
make-sparse-vector: Public ordinary functions
make-vec: Public ordinary functions
mean-vector: Private ordinary functions
Method, (setf argument-error-message): Private generic functions
Method, argument-error-message: Private generic functions
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods
Method, print-object: Public standalone methods

N
n-class-of: Public ordinary functions

O
one-vs-one-clear-functions-for-store: Private ordinary functions
one-vs-one-input-dimension: Private ordinary functions
one-vs-one-learner-predict: Private ordinary functions
one-vs-one-learner-update: Private ordinary functions
one-vs-one-learners-vector: Private ordinary functions
one-vs-one-n-class: Private ordinary functions
one-vs-one-p: Private ordinary functions
one-vs-one-predict: Public ordinary functions
one-vs-one-restore-functions: Private ordinary functions
one-vs-one-test: Public ordinary functions
one-vs-one-train: Public ordinary functions
one-vs-one-update: Public ordinary functions
one-vs-rest-clear-functions-for-store: Private ordinary functions
one-vs-rest-input-dimension: Private ordinary functions
one-vs-rest-learner-activate: Private ordinary functions
one-vs-rest-learner-bias: Private ordinary functions
one-vs-rest-learner-update: Private ordinary functions
one-vs-rest-learner-weight: Private ordinary functions
one-vs-rest-learners-vector: Private ordinary functions
one-vs-rest-n-class: Private ordinary functions
one-vs-rest-p: Private ordinary functions
one-vs-rest-predict: Public ordinary functions
one-vs-rest-restore-functions: Private ordinary functions
one-vs-rest-test: Public ordinary functions
one-vs-rest-train: Public ordinary functions
one-vs-rest-update: Public ordinary functions

P
perceptron-bias: Private ordinary functions
perceptron-input-dimension: Private ordinary functions
perceptron-p: Private ordinary functions
perceptron-predict: Public ordinary functions
perceptron-test: Public ordinary functions
perceptron-tmp-float: Private ordinary functions
perceptron-train: Public ordinary functions
perceptron-update: Public ordinary functions
perceptron-weight: Private ordinary functions
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
print-object: Public standalone methods
probit: Private ordinary functions
ps-v*n: Public ordinary functions

R
read-data: Public ordinary functions
read-datum: Private ordinary functions
read-datum-sparse: Private ordinary functions
restore: Public ordinary functions
rls-bias: Private ordinary functions
rls-gamma: Private ordinary functions
rls-input-dimension: Private ordinary functions
rls-p: Private ordinary functions
rls-predict: Public ordinary functions
rls-sigma: Private ordinary functions
rls-sigma0: Private ordinary functions
rls-test: Public ordinary functions
rls-tmp-float: Private ordinary functions
rls-tmp-vec1: Private ordinary functions
rls-tmp-vec2: Private ordinary functions
rls-train: Public ordinary functions
rls-update: Public ordinary functions
rls-weight: Private ordinary functions

S
s-v*n: Public ordinary functions
sanity-check: Private ordinary functions
save: Public ordinary functions
scw-bias: Private ordinary functions
scw-c: Private ordinary functions
scw-eta: Private ordinary functions
scw-input-dimension: Private ordinary functions
scw-p: Private ordinary functions
scw-phi: Private ordinary functions
scw-predict: Public ordinary functions
scw-psi: Private ordinary functions
scw-sigma: Private ordinary functions
scw-sigma0: Private ordinary functions
scw-test: Public ordinary functions
scw-tmp-float: Private ordinary functions
scw-tmp-vec1: Private ordinary functions
scw-tmp-vec2: Private ordinary functions
scw-train: Public ordinary functions
scw-update: Public ordinary functions
scw-weight: Private ordinary functions
scw-zeta: Private ordinary functions
sf: Private ordinary functions
sf!: Private ordinary functions
shuffle-vector: Public ordinary functions
sigmoid: Private macros
sign: Private ordinary functions
sparse-arow-bias: Private ordinary functions
sparse-arow-gamma: Private ordinary functions
sparse-arow-input-dimension: Private ordinary functions
sparse-arow-p: Private ordinary functions
sparse-arow-predict: Public ordinary functions
sparse-arow-sigma: Private ordinary functions
sparse-arow-sigma0: Private ordinary functions
sparse-arow-test: Public ordinary functions
sparse-arow-tmp-float: Private ordinary functions
sparse-arow-tmp-vec1: Private ordinary functions
sparse-arow-tmp-vec2: Private ordinary functions
sparse-arow-train: Public ordinary functions
sparse-arow-update: Public ordinary functions
sparse-arow-weight: Private ordinary functions
sparse-learner?: Public ordinary functions
sparse-lr+adam-alpha: Private ordinary functions
sparse-lr+adam-beta1: Private ordinary functions
sparse-lr+adam-beta1^t: Private ordinary functions
sparse-lr+adam-beta2: Private ordinary functions
sparse-lr+adam-beta2^t: Private ordinary functions
sparse-lr+adam-bias: Private ordinary functions
sparse-lr+adam-c: Private ordinary functions
sparse-lr+adam-epsilon: Private ordinary functions
sparse-lr+adam-g: Private ordinary functions
sparse-lr+adam-input-dimension: Private ordinary functions
sparse-lr+adam-m: Private ordinary functions
sparse-lr+adam-m0: Private ordinary functions
sparse-lr+adam-p: Private ordinary functions
sparse-lr+adam-predict: Public ordinary functions
sparse-lr+adam-test: Public ordinary functions
sparse-lr+adam-tmp-float: Private ordinary functions
sparse-lr+adam-tmp-vec: Private ordinary functions
sparse-lr+adam-train: Public ordinary functions
sparse-lr+adam-update: Public ordinary functions
sparse-lr+adam-v: Private ordinary functions
sparse-lr+adam-v0: Private ordinary functions
sparse-lr+adam-weight: Private ordinary functions
sparse-lr+sgd-bias: Private ordinary functions
sparse-lr+sgd-c: Private ordinary functions
sparse-lr+sgd-eta: Private ordinary functions
sparse-lr+sgd-g: Private ordinary functions
sparse-lr+sgd-input-dimension: Private ordinary functions
sparse-lr+sgd-p: Private ordinary functions
sparse-lr+sgd-predict: Public ordinary functions
sparse-lr+sgd-test: Public ordinary functions
sparse-lr+sgd-tmp-float: Private ordinary functions
sparse-lr+sgd-tmp-vec: Private ordinary functions
sparse-lr+sgd-train: Public ordinary functions
sparse-lr+sgd-update: Public ordinary functions
sparse-lr+sgd-weight: Private ordinary functions
sparse-perceptron-bias: Private ordinary functions
sparse-perceptron-input-dimension: Private ordinary functions
sparse-perceptron-p: Private ordinary functions
sparse-perceptron-predict: Public ordinary functions
sparse-perceptron-test: Public ordinary functions
sparse-perceptron-tmp-float: Private ordinary functions
sparse-perceptron-train: Public ordinary functions
sparse-perceptron-update: Public ordinary functions
sparse-perceptron-weight: Private ordinary functions
sparse-rls-bias: Private ordinary functions
sparse-rls-gamma: Private ordinary functions
sparse-rls-input-dimension: Private ordinary functions
sparse-rls-p: Private ordinary functions
sparse-rls-predict: Public ordinary functions
sparse-rls-sigma: Private ordinary functions
sparse-rls-sigma0: Private ordinary functions
sparse-rls-test: Public ordinary functions
sparse-rls-tmp-float: Private ordinary functions
sparse-rls-tmp-vec1: Private ordinary functions
sparse-rls-tmp-vec2: Private ordinary functions
sparse-rls-train: Public ordinary functions
sparse-rls-update: Public ordinary functions
sparse-rls-weight: Private ordinary functions
sparse-scw-bias: Private ordinary functions
sparse-scw-c: Private ordinary functions
sparse-scw-eta: Private ordinary functions
sparse-scw-input-dimension: Private ordinary functions
sparse-scw-p: Private ordinary functions
sparse-scw-phi: Private ordinary functions
sparse-scw-predict: Public ordinary functions
sparse-scw-psi: Private ordinary functions
sparse-scw-sigma: Private ordinary functions
sparse-scw-sigma0: Private ordinary functions
sparse-scw-test: Public ordinary functions
sparse-scw-tmp-float: Private ordinary functions
sparse-scw-tmp-vec1: Private ordinary functions
sparse-scw-tmp-vec2: Private ordinary functions
sparse-scw-train: Public ordinary functions
sparse-scw-update: Public ordinary functions
sparse-scw-weight: Private ordinary functions
sparse-scw-zeta: Private ordinary functions
sparse-symbol?: Private ordinary functions
sparse-vector-index-vector: Public ordinary functions
sparse-vector-length: Public ordinary functions
sparse-vector-p: Private ordinary functions
sparse-vector-value-vector: Public ordinary functions
split-lambda-list: Private ordinary functions
sps-v*n: Public ordinary functions
standard-deviation-vector: Private ordinary functions
sum-permutation: Private ordinary functions

T
test: Public ordinary functions
to-float: Public ordinary functions
to-int: Public ordinary functions
train: Public ordinary functions

V
v*: Public ordinary functions
v*n: Public ordinary functions
v+: Public ordinary functions
v+n: Public ordinary functions
v-: Public ordinary functions
v-sqrt: Public ordinary functions
v/: Public ordinary functions


A.3 Variables

Jump to:   A   B   C   E   G   I   L   M   N   P   S   T   V   W   Z  
Index Entry  Section

A
alpha: Private structures
alpha: Private structures
argument-error-message: Private conditions

B
beta1: Private structures
beta1: Private structures
beta1^t: Private structures
beta1^t: Private structures
beta2: Private structures
beta2: Private structures
beta2^t: Private structures
beta2^t: Private structures
bias: Private structures
bias: Private structures
bias: Private structures
bias: Private structures
bias: Private structures
bias: Private structures
bias: Private structures
bias: Private structures
bias: Private structures
bias: Private structures
bias: Private structures
bias: Private structures

C
c: Private structures
c: Private structures
c: Private structures
c: Private structures
c: Private structures
c: Private structures

E
epsilon: Private structures
epsilon: Private structures
eta: Private structures
eta: Private structures
eta: Private structures
eta: Private structures

G
g: Private structures
g: Private structures
g: Private structures
g: Private structures
gamma: Private structures
gamma: Private structures
gamma: Private structures
gamma: Private structures

I
index-vector: Public structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures
input-dimension: Private structures

L
learner-activate: Private structures
learner-bias: Private structures
learner-predict: Private structures
learner-update: Private structures
learner-update: Private structures
learner-weight: Private structures
learners-vector: Private structures
learners-vector: Private structures
length: Public structures

M
m: Private structures
m: Private structures
m0: Private structures
m0: Private structures

N
n-class: Private structures
n-class: Private structures

P
phi: Private structures
phi: Private structures
psi: Private structures
psi: Private structures

S
sigma: Private structures
sigma: Private structures
sigma: Private structures
sigma: Private structures
sigma: Private structures
sigma: Private structures
sigma0: Private structures
sigma0: Private structures
sigma0: Private structures
sigma0: Private structures
sigma0: Private structures
sigma0: Private structures
Slot, alpha: Private structures
Slot, alpha: Private structures
Slot, argument-error-message: Private conditions
Slot, beta1: Private structures
Slot, beta1: Private structures
Slot, beta1^t: Private structures
Slot, beta1^t: Private structures
Slot, beta2: Private structures
Slot, beta2: Private structures
Slot, beta2^t: Private structures
Slot, beta2^t: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, bias: Private structures
Slot, c: Private structures
Slot, c: Private structures
Slot, c: Private structures
Slot, c: Private structures
Slot, c: Private structures
Slot, c: Private structures
Slot, epsilon: Private structures
Slot, epsilon: Private structures
Slot, eta: Private structures
Slot, eta: Private structures
Slot, eta: Private structures
Slot, eta: Private structures
Slot, g: Private structures
Slot, g: Private structures
Slot, g: Private structures
Slot, g: Private structures
Slot, gamma: Private structures
Slot, gamma: Private structures
Slot, gamma: Private structures
Slot, gamma: Private structures
Slot, index-vector: Public structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, input-dimension: Private structures
Slot, learner-activate: Private structures
Slot, learner-bias: Private structures
Slot, learner-predict: Private structures
Slot, learner-update: Private structures
Slot, learner-update: Private structures
Slot, learner-weight: Private structures
Slot, learners-vector: Private structures
Slot, learners-vector: Private structures
Slot, length: Public structures
Slot, m: Private structures
Slot, m: Private structures
Slot, m0: Private structures
Slot, m0: Private structures
Slot, n-class: Private structures
Slot, n-class: Private structures
Slot, phi: Private structures
Slot, phi: Private structures
Slot, psi: Private structures
Slot, psi: Private structures
Slot, sigma: Private structures
Slot, sigma: Private structures
Slot, sigma: Private structures
Slot, sigma: Private structures
Slot, sigma: Private structures
Slot, sigma: Private structures
Slot, sigma0: Private structures
Slot, sigma0: Private structures
Slot, sigma0: Private structures
Slot, sigma0: Private structures
Slot, sigma0: Private structures
Slot, sigma0: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-float: Private structures
Slot, tmp-vec: Private structures
Slot, tmp-vec: Private structures
Slot, tmp-vec: Private structures
Slot, tmp-vec: Private structures
Slot, tmp-vec1: Private structures
Slot, tmp-vec1: Private structures
Slot, tmp-vec1: Private structures
Slot, tmp-vec1: Private structures
Slot, tmp-vec1: Private structures
Slot, tmp-vec1: Private structures
Slot, tmp-vec2: Private structures
Slot, tmp-vec2: Private structures
Slot, tmp-vec2: Private structures
Slot, tmp-vec2: Private structures
Slot, tmp-vec2: Private structures
Slot, tmp-vec2: Private structures
Slot, v: Private structures
Slot, v: Private structures
Slot, v0: Private structures
Slot, v0: Private structures
Slot, value-vector: Public structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, weight: Private structures
Slot, zeta: Private structures
Slot, zeta: Private structures

T
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-float: Private structures
tmp-vec: Private structures
tmp-vec: Private structures
tmp-vec: Private structures
tmp-vec: Private structures
tmp-vec1: Private structures
tmp-vec1: Private structures
tmp-vec1: Private structures
tmp-vec1: Private structures
tmp-vec1: Private structures
tmp-vec1: Private structures
tmp-vec2: Private structures
tmp-vec2: Private structures
tmp-vec2: Private structures
tmp-vec2: Private structures
tmp-vec2: Private structures
tmp-vec2: Private structures

V
v: Private structures
v: Private structures
v0: Private structures
v0: Private structures
value-vector: Public structures

W
weight: Private structures
weight: Private structures
weight: Private structures
weight: Private structures
weight: Private structures
weight: Private structures
weight: Private structures
weight: Private structures
weight: Private structures
weight: Private structures
weight: Private structures
weight: Private structures

Z
zeta: Private structures
zeta: Private structures


A.4 Data types

Jump to:   A   C   F   L   M   O   P   R   S   U   V  
Index Entry  Section

A
argument-error: Private conditions
arow: Private structures

C
cl-online-learning: The cl-online-learning system
cl-online-learning: The cl-online-learning package
cl-online-learning-asd: The cl-online-learning-asd package
cl-online-learning.asd: The cl-online-learning/cl-online-learning․asd file
cl-online-learning.lisp: The cl-online-learning/src/cl-online-learning․lisp file
cl-online-learning.utils: The cl-online-learning․utils package
cl-online-learning.vector: The cl-online-learning․vector package
Condition, argument-error: Private conditions

F
File, cl-online-learning.asd: The cl-online-learning/cl-online-learning․asd file
File, cl-online-learning.lisp: The cl-online-learning/src/cl-online-learning․lisp file
File, rls.lisp: The cl-online-learning/src/rls․lisp file
File, utils.lisp: The cl-online-learning/src/utils․lisp file
File, vector.lisp: The cl-online-learning/src/vector․lisp file

L
lr+adam: Private structures
lr+sgd: Private structures

M
Module, src: The cl-online-learning/src module

O
one-vs-one: Private structures
one-vs-rest: Private structures

P
Package, cl-online-learning: The cl-online-learning package
Package, cl-online-learning-asd: The cl-online-learning-asd package
Package, cl-online-learning.utils: The cl-online-learning․utils package
Package, cl-online-learning.vector: The cl-online-learning․vector package
perceptron: Private structures

R
rls: Private structures
rls.lisp: The cl-online-learning/src/rls․lisp file

S
scw: Private structures
sparse-arow: Private structures
sparse-lr+adam: Private structures
sparse-lr+sgd: Private structures
sparse-perceptron: Private structures
sparse-rls: Private structures
sparse-scw: Private structures
sparse-vector: Public structures
src: The cl-online-learning/src module
Structure, arow: Private structures
Structure, lr+adam: Private structures
Structure, lr+sgd: Private structures
Structure, one-vs-one: Private structures
Structure, one-vs-rest: Private structures
Structure, perceptron: Private structures
Structure, rls: Private structures
Structure, scw: Private structures
Structure, sparse-arow: Private structures
Structure, sparse-lr+adam: Private structures
Structure, sparse-lr+sgd: Private structures
Structure, sparse-perceptron: Private structures
Structure, sparse-rls: Private structures
Structure, sparse-scw: Private structures
Structure, sparse-vector: Public structures
System, cl-online-learning: The cl-online-learning system

U
utils.lisp: The cl-online-learning/src/utils․lisp file

V
vector.lisp: The cl-online-learning/src/vector․lisp file