The cl-svm Reference Manual

This is the cl-svm Reference Manual, version 2.9, generated automatically by Declt version 4.0 beta 2 "William Riker" on Sat Dec 03 20:43:35 2022 GMT+0.

Table of Contents


1 Introduction


2 Systems

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


2.1 cl-svm

Author

Red Daly <>

License

Communist license

Version

2.9

Source

cl-svm.asd.

Child Component

src (module).


3 Modules

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


3.1 cl-svm/src

Source

cl-svm.asd.

Parent Component

cl-svm (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-svm/cl-svm.asd

Source

cl-svm.asd.

Parent Component

cl-svm (system).

ASDF Systems

cl-svm.

Packages

cl-svm-system.


4.1.2 cl-svm/src/package.lisp

Source

cl-svm.asd.

Parent Component

src (module).

Packages

cl-svm.


4.1.3 cl-svm/src/svm.lisp

Dependency

package.lisp (file).

Source

cl-svm.asd.

Parent Component

src (module).

Public Interface
Internals

*debug-output* (special variable).


5 Packages

Packages are listed by definition order.


5.1 cl-svm

Source

package.lisp.

Nickname

svm

Use List

common-lisp.

Public Interface
Internals

*debug-output* (special variable).


5.2 cl-svm-system

Source

cl-svm.asd.

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

6 Definitions

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


6.1 Public Interface


6.1.1 Macros

Macro: training-pair-bind ((x-var y-var) training-pair &body body)

Binds the symbols named by x-var and y-var to the x and y components of a training pair.

Package

cl-svm.

Source

svm.lisp.


6.1.2 Ordinary functions

Function: dot-product (v1 v2)
Package

cl-svm.

Source

svm.lisp.

Function: train-svm (training-pairs &key kkt-tolerance kernel c)

Trains a simple SVM using an arbitrary kernel. Training-pairs is a sequence
of of pairs, where the car of each pair is a vector of numbers and the cdr is either -1 or 1.

This will return three values: The first value is a function that can be called with
an argument of the same dimension as a training example. It will return either t
or nil.

The other two return values are the vector w and the scalar b that define the plane of the form w . x - b = 0.

Implementation note:
The algorithm used to optimize the SVM is the SMO algorithm first described by Platt. It is actually not even that algorithm, yet, because we apply no heuristic to choose which constraints to optimize–we just select random ones. Also we do not account
for the case where n=0 in the code below, which is done in the actual SMO algorithm.

Package

cl-svm.

Source

svm.lisp.


6.2 Internals


6.2.1 Special variables

Special Variable: *debug-output*
Package

cl-svm.

Source

svm.lisp.


Appendix A Indexes


A.1 Concepts


A.3 Variables

Jump to:   *  
S  
Index Entry  Section

*
*debug-output*: Private special variables

S
Special Variable, *debug-output*: Private special variables