The clusters Reference Manual

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The clusters Reference Manual

This is the clusters Reference Manual, version 1.0.0, generated automatically by Declt version 4.0 beta 2 "William Riker" on Thu Sep 15 04:26:18 2022 GMT+0.

Table of Contents


1 Introduction

clusters

Variety of clustering tools for the Common Lisp

Distances

Package clusters.distance presentes distance functions, intended for use in clustering algorithms. This includes:

Metrics

Package clusters.metric also presents functions intended for use in clustering algorithms, However, these functions also happen to be true metrics.

Clustering algorithms

Each clustering algorithm has its own package exporting PARAMETERS symbol. This symbol names the class used to hold the algorithm parameters. To use the algorithm, first construct instance of this class, then call CLUSTER function passing the PARAMETERS instance into it along with the DATA. The returned object contains the clusters, and they can be extracted using the CLUSTER-CONTENTS function. The following example has been taken from the tests.

(defun metric (a b)
  (coerce (abs (- a b))
          'single-float))

(let* ((data (~> (concatenate 'vector
                              (iota 100 :start 0)
                              (iota 300 :start 500)
                              (iota 100 :start 200))
                 shuffle))
       (parameters (make-instance 'clusters.clarans:parameters
                                  :parallelp nil
                                  :medoids-count 10
                                  :max-neighbor 200
                                  :distance-function #'metric))
       (clusters (clusters:cluster parameters data))
       (cluster-contents (clusters:cluster-contents clusters)))
    ...)

All PARAMETERS classes contain slots intended bootsrapping silhouette values for the clusters. To obtain the silhouette value from the clustering results simply call the CLUSTERS:SILHOUETTE function. This is particulary useful if you are attempting to find the optimal number of clusters.

PARALLELP

Majority of the algorithms in this system have rudementary parallelization, made with the ever so useful LPARALLEL library. Please notice, that this means that (unless you are certain that NIL has been passed as :PARALLELP value) you must avoid calling CLUSTER on the LPARALLEL worker thread. Otherwise: deadlocks.

Silhouette

You can use clusters:silhouette to obtain silhouette values for each of the constructed clusters.


2 Systems

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


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2.1 clusters

Cluster algorithms in CL, for CL.

Maintainer

Marek Kochanowicz

Author

Marek Kochanowicz

License

BSD simplified

Version

1.0.0

Dependencies
  • iterate (system).
  • alexandria (system).
  • serapeum (system).
  • documentation-utils-extensions (system).
  • metabang-bind (system).
  • bordeaux-threads (system).
  • lparallel (system).
  • cl-data-structures (system).
Source

clusters.asd.

Child Components

3 Modules

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


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3.1 clusters/utils

Dependency

aux-package.lisp (file).

Source

clusters.asd.

Parent Component

clusters (system).

Child Components

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3.2 clusters/metric

Dependency

utils (module).

Source

clusters.asd.

Parent Component

clusters (system).

Child Components

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3.3 clusters/distance

Dependency

metric (module).

Source

clusters.asd.

Parent Component

clusters (system).

Child Components

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3.4 clusters/common

Dependency

distance (module).

Source

clusters.asd.

Parent Component

clusters (system).

Child Components

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3.5 clusters/pam

Dependency

common (module).

Source

clusters.asd.

Parent Component

clusters (system).

Child Components

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3.6 clusters/clarans

Dependency

pam (module).

Source

clusters.asd.

Parent Component

clusters (system).

Child Components

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3.7 clusters/k-means

Dependency

clarans (module).

Source

clusters.asd.

Parent Component

clusters (system).

Child Components

4 Files

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


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4.1 Lisp


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4.1.1 clusters/clusters.asd

Source

clusters.asd.

Parent Component

clusters (system).

ASDF Systems

clusters.


4.1.2 clusters/aux-package.lisp

Source

clusters.asd.

Parent Component

clusters (system).

Packages
Public Interface

defpackage (macro).


4.1.3 clusters/utils/package.lisp

Source

clusters.asd.

Parent Component

utils (module).

Packages

clusters.utils.


4.1.4 clusters/utils/maps.lisp

Source

clusters.asd.

Parent Component

utils (module).

Public Interface

4.1.5 clusters/utils/matrix.lisp

Source

clusters.asd.

Parent Component

utils (module).

Public Interface
Internals

4.1.6 clusters/utils/random.lisp

Source

clusters.asd.

Parent Component

utils (module).

Public Interface

4.1.7 clusters/utils/utils.lisp

Source

clusters.asd.

Parent Component

utils (module).

Public Interface

4.1.8 clusters/utils/partition.lisp

Source

clusters.asd.

Parent Component

utils (module).

Public Interface

seed (function).


4.1.9 clusters/metric/package.lisp

Source

clusters.asd.

Parent Component

metric (module).

Packages

clusters.metric.


4.1.10 clusters/metric/docstrings.lisp

Source

clusters.asd.

Parent Component

metric (module).


4.1.11 clusters/metric/euclid.lisp

Source

clusters.asd.

Parent Component

metric (module).

Public Interface

euclid (function).


4.1.12 clusters/metric/svr.lisp

Source

clusters.asd.

Parent Component

metric (module).

Public Interface

svr (function).

Internals

4.1.13 clusters/metric/levenshtein.lisp

Source

clusters.asd.

Parent Component

metric (module).

Public Interface

levenshtein (function).


4.1.14 clusters/metric/lcs.lisp

Source

clusters.asd.

Parent Component

metric (module).

Public Interface

lcs (function).


4.1.15 clusters/metric/hellinger.lisp

Source

clusters.asd.

Parent Component

metric (module).

Public Interface

hellinger (function).

Internals

+sqrt2+ (constant).


4.1.16 clusters/metric/earth-mover.lisp

Source

clusters.asd.

Parent Component

metric (module).

Internals

earth-mover-metric (function).


4.1.17 clusters/metric/average.lisp

Source

clusters.asd.

Parent Component

metric (module).

Public Interface

average (function).


4.1.18 clusters/metric/group-average.lisp

Source

clusters.asd.

Parent Component

metric (module).

Public Interface

group-average (function).


4.1.19 clusters/metric/hausdorff.lisp

Source

clusters.asd.

Parent Component

metric (module).

Public Interface

hausdorff (function).


4.1.20 clusters/distance/package.lisp

Source

clusters.asd.

Parent Component

distance (module).

Packages

clusters.distance.


4.1.21 clusters/distance/docstrings.lisp

Source

clusters.asd.

Parent Component

distance (module).


4.1.22 clusters/distance/bhattacharyya.lisp

Source

clusters.asd.

Parent Component

distance (module).

Public Interface

bhattacharyya (function).


4.1.23 clusters/distance/sinkhorn.lisp

Source

clusters.asd.

Parent Component

distance (module).

Public Interface

sinkhorn (function).

Internals

4.1.24 clusters/common/package.lisp

Source

clusters.asd.

Parent Component

common (module).

Packages

clusters.


4.1.25 clusters/common/generics.lisp

Source

clusters.asd.

Parent Component

common (module).

Public Interface
Internals

parallel-p (generic function).


4.1.26 clusters/common/types.lisp

Source

clusters.asd.

Parent Component

common (module).

Public Interface
Internals

parameters-holder (class).


4.1.27 clusters/common/utils.lisp

Source

clusters.asd.

Parent Component

common (module).

Internals

cluster-values (function).


4.1.28 clusters/common/functions.lisp

Source

clusters.asd.

Parent Component

common (module).

Public Interface

4.1.29 clusters/common/silhouette.lisp

Source

clusters.asd.

Parent Component

common (module).

Public Interface

silhouette (reader method).

Internals

4.1.30 clusters/common/methods.lisp

Source

clusters.asd.

Parent Component

common (module).

Public Interface

4.1.31 clusters/pam/package.lisp

Source

clusters.asd.

Parent Component

pam (module).

Packages

clusters.pam.


4.1.32 clusters/pam/generics.lisp

Source

clusters.asd.

Parent Component

pam (module).


4.1.33 clusters/pam/types.lisp

Source

clusters.asd.

Parent Component

pam (module).

Public Interface

parameters (class).

Internals

4.1.34 clusters/pam/utils.lisp

Source

clusters.asd.

Parent Component

pam (module).

Internals

4.1.35 clusters/pam/methods.lisp

Source

clusters.asd.

Parent Component

pam (module).

Public Interface
Internals

4.1.36 clusters/clarans/package.lisp

Source

clusters.asd.

Parent Component

clarans (module).

Packages

clusters.clarans.


4.1.37 clusters/clarans/generics.lisp

Source

clusters.asd.

Parent Component

clarans (module).

Internals

4.1.38 clusters/clarans/types.lisp

Source

clusters.asd.

Parent Component

clarans (module).

Public Interface
Internals

4.1.39 clusters/clarans/utils.lisp

Source

clusters.asd.

Parent Component

clarans (module).

Internals

4.1.40 clusters/clarans/methods.lisp

Source

clusters.asd.

Parent Component

clarans (module).

Public Interface
Internals

4.1.41 clusters/k-means/package.lisp

Source

clusters.asd.

Parent Component

k-means (module).

Packages

clusters.k-means.


4.1.42 clusters/k-means/types.lisp

Source

clusters.asd.

Parent Component

k-means (module).

Public Interface

parameters (class).

Internals

4.1.43 clusters/k-means/utils.lisp

Source

clusters.asd.

Parent Component

k-means (module).

Internals

4.1.44 clusters/k-means/methods.lisp

Source

clusters.asd.

Parent Component

k-means (module).

Public Interface
Internals

5 Packages

Packages are listed by definition order.


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5.1 clusters

Source

package.lisp.

Use List
Public Interface
Internals

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5.2 clusters.fancy

Source

aux-package.lisp.

Public Interface

defpackage (macro).


5.3 clusters.utils

Source

package.lisp.

Use List
Public Interface
Internals

5.5 clusters.pam

Source

package.lisp.

Use List
Public Interface

parameters (class).

Internals

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5.6 clusters.clarans

Source

package.lisp.

Use List
Public Interface

parameters (class).

Internals

5.7 clusters.distance

Source

package.lisp.

Use List
Public Interface
Internals

5.8 clusters.metric

Source

package.lisp.

Use List
Public Interface
Internals

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5.9 clusters.k-means

Source

package.lisp.

Use List
Public Interface

parameters (class).

Internals

6 Definitions

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


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6.1 Public Interface


6.1.1 Macros

Macro: defpackage (package &rest options)
Package

clusters.fancy.

Source

aux-package.lisp.


6.1.2 Ordinary functions

Function: average (fn a b &key test key)
Package

clusters.metric.

Source

average.lisp.

Function: bhattacharyya (h1 h2)
Package

clusters.distance.

Source

bhattacharyya.lisp.

Function: calculate-silhouette (result &optional distance-matrix)
Package

clusters.

Source

functions.lisp.

Function: cluster (parameters data &rest arguments)
Package

clusters.

Source

functions.lisp.

Function: copy-into (destination source)
Package

clusters.utils.

Source

utils.lisp.

Function: distance-matrix (parallel distance-function data)
Package

clusters.utils.

Source

matrix.lisp.

Function: draw-random-vector (input size &optional result)
Package

clusters.utils.

Source

random.lisp.

Function: euclid (a b)
Package

clusters.metric.

Source

euclid.lisp.

Function: group-average (fn a b &key key element-type distance-matrix)
Package

clusters.metric.

Source

group-average.lisp.

Function: half-matrix-index->square-row/column (count index)
Package

clusters.utils.

Source

matrix.lisp.

Function: half-matrix-size->count (size)
Package

clusters.utils.

Source

matrix.lisp.

Function: hausdorff (fn a b &key key element-type distance-matrix)
Package

clusters.metric.

Source

hausdorff.lisp.

Function: hellinger (q p)
Package

clusters.metric.

Source

hellinger.lisp.

Function: lazy-shuffle (from to)
Package

clusters.utils.

Source

random.lisp.

Function: lcs (a b &key test key a-start a-end b-start b-end base)
Package

clusters.metric.

Source

lcs.lisp.

Function: levenshtein (str1 str2)
Package

clusters.metric.

Source

levenshtein.lisp.

Function: make-algorithm-state (parameters data &rest arguments)
Package

clusters.

Source

functions.lisp.

Function: make-half-matrix (count &rest all &key element-type initial-element initial-contents)
Package

clusters.utils.

Source

matrix.lisp.

Function: map-into-half-matrix (parallel half-matrix function)
Package

clusters.utils.

Source

matrix.lisp.

Function: mref (half-matrix from to &optional count)
Package

clusters.utils.

Source

matrix.lisp.

Function: (setf mref) (half-matrix from to &optional count)
Package

clusters.utils.

Source

matrix.lisp.

Function: obtain-result (state)
Package

clusters.

Source

functions.lisp.

Function: pmap (parallel type function &rest sequences)
Package

clusters.utils.

Source

maps.lisp.

Function: pmap-into (parallel sequence function &rest sequences)
Package

clusters.utils.

Source

maps.lisp.

Function: seed (data indexes medoids y distance-function)
Package

clusters.utils.

Source

partition.lisp.

Function: sinkhorn (cost first-vector second-vector regularization-strength &optional epsilon)
Package

clusters.distance.

Source

sinkhorn.lisp.

Function: square-row/column->half-matrix-index (count j i)
Package

clusters.utils.

Source

matrix.lisp.

Function: svr (a b)
Package

clusters.metric.

Source

svr.lisp.

Function: swap-if (vector test &key key start end)
Package

clusters.utils.

Source

utils.lisp.

Function: transform (parallel function sequence &rest sequences)
Package

clusters.utils.

Source

maps.lisp.


6.1.3 Generic functions

Generic Function: algorithm-state-class (parameters)
Package

clusters.

Source

generics.lisp.

Methods
Method: algorithm-state-class ((parameters parameters))
Source

methods.lisp.

Method: algorithm-state-class ((parameters parameters))
Source

methods.lisp.

Method: algorithm-state-class ((parameters parameters))
Source

methods.lisp.

Generic Function: algorithm-state-initialization-list (parameters data &rest arguments &key distance-matrix &allow-other-keys)
Package

clusters.

Source

generics.lisp.

Method Combination

append.

Options

:most-specific-first

Methods
Method: algorithm-state-initialization-list append ((parameters parameters) data &rest all &key &allow-other-keys)
Source

methods.lisp.

Method: algorithm-state-initialization-list append ((parameters parameters) data &rest all &key distance-matrix &allow-other-keys)
Source

methods.lisp.

Method: algorithm-state-initialization-list append ((parameters parameters) data &rest arguments &key &allow-other-keys)
Source

methods.lisp.

Generic Function: calculate-silhouette* (parameters result &optional distance-matrix)
Package

clusters.

Source

generics.lisp.

Methods
Method: calculate-silhouette* :around ((parameters parameters) clustering-result &optional distance-matrix)
Source

methods.lisp.

Method: calculate-silhouette* ((parameters parameters) clustering-result &optional distance-matrix)
Source

methods.lisp.

Generic Function: cluster-contents (result)
Package

clusters.

Source

generics.lisp.

Methods
Method: cluster-contents ((result result))
Source

methods.lisp.

Generic Reader: cluster-indexes (result)
Package

clusters.

Source

generics.lisp.

Methods
Reader Method: cluster-indexes ((result result))

automatically generated reader method

Source

types.lisp.

Target Slot

%cluster-indexes.

Generic Reader: data (result)
Package

clusters.

Source

generics.lisp.

Methods
Reader Method: data ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%data.

Reader Method: data ((result result))

automatically generated reader method

Source

types.lisp.

Target Slot

%data.

Generic Writer: (setf data) (algorithm-state)
Package

clusters.

Source

generics.lisp.

Methods
Writer Method: (setf data) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%data.

Generic Function: distance-function (instance)
Package

clusters.

Methods
Method: distance-function ((parameters parameters))
Source

methods.lisp.

Reader Method: distance-function ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%distance-function.

Method: distance-function ((instance parameters-holder))
Source

methods.lisp.

Generic Reader: indexes (algorithm-state)
Package

clusters.

Source

generics.lisp.

Methods
Reader Method: indexes ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%indexes.

Reader Method: indexes ((result result))

automatically generated reader method

Source

types.lisp.

Target Slot

%indexes.

Generic Writer: (setf indexes) (algorithm-state)
Package

clusters.

Source

generics.lisp.

Methods
Writer Method: (setf indexes) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%indexes.

Generic Function: key-function (parameters)
Package

clusters.

Source

generics.lisp.

Methods
Method: key-function ((instance parameters-holder))
Source

methods.lisp.

Reader Method: key-function ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%key-function.

Generic Function: parallelp (object)
Package

clusters.

Methods
Method: parallelp ((instance parameters-holder))
Source

methods.lisp.

Reader Method: parallelp ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%parallelp.

Generic Reader: parameters (result)
Package

clusters.

Source

generics.lisp.

Methods
Reader Method: parameters ((parameters-holder parameters-holder))

automatically generated reader method

Source

types.lisp.

Target Slot

%parameters.

Generic Function: result-class (parameters)
Package

clusters.

Source

generics.lisp.

Methods
Method: result-class ((parameters parameters))
Source

methods.lisp.

Method: result-class ((state algorithm-state))
Source

methods.lisp.

Method: result-class ((parameters parameters))
Source

methods.lisp.

Generic Function: result-initialization-list (state)
Package

clusters.

Source

generics.lisp.

Method Combination

append.

Options

:most-specific-first

Methods
Method: result-initialization-list append ((state algorithm-state))
Source

methods.lisp.

Method: result-initialization-list append ((state algorithm-state))
Source

methods.lisp.

Method: result-initialization-list append ((state algorithm-state))
Source

methods.lisp.

Method: result-initialization-list append ((state algorithm-state))
Source

methods.lisp.

Generic Function: run-algorithm (state)
Package

clusters.

Source

generics.lisp.

Methods
Method: run-algorithm ((state algorithm-state))
Source

methods.lisp.

Method: run-algorithm ((state algorithm-state))
Source

methods.lisp.

Method: run-algorithm ((state algorithm-state))
Source

methods.lisp.

Generic Function: silhouette (result)
Package

clusters.

Source

generics.lisp.

Methods
Reader Method: silhouette :before ((object result))
Source

silhouette.lisp.

Target Slot

%silhouette.

Method: silhouette ((result result))

automatically generated reader method

Source

types.lisp.

Generic Function: silhouette-sample-count (object)
Package

clusters.

Methods
Method: silhouette-sample-count ((instance parameters-holder))
Source

methods.lisp.

Reader Method: silhouette-sample-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%silhouette-sample-count.

Generic Function: silhouette-sample-size (object)
Package

clusters.

Methods
Method: silhouette-sample-size ((instance parameters-holder))
Source

methods.lisp.

Reader Method: silhouette-sample-size ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%silhouette-sample-size.


6.1.4 Standalone methods

Method: initialize-instance :after ((instance algorithm-state) &rest initargs)
Source

methods.lisp.

Method: initialize-instance :after ((instance parameters) &rest all)
Source

methods.lisp.

Method: initialize-instance :after ((instance algorithm-state) &rest initargs)
Source

methods.lisp.

Method: initialize-instance :after ((instance parameters) &rest all)
Source

methods.lisp.

Method: initialize-instance :after ((instance algorithm-state) &rest all)
Source

methods.lisp.

Method: initialize-instance :after ((instance parameters) &rest all)
Source

methods.lisp.

Method: initialize-instance :after ((instance algorithm-state) &rest all)
Source

methods.lisp.


6.1.5 Classes

Class: algorithm-state
Package

clusters.

Source

types.lisp.

Direct superclasses

parameters-holder.

Direct subclasses
Direct methods
Direct Default Initargs
InitargValue
:data(vect)
:indexesnil
Direct slots
Slot: %data
Initargs

:data

Readers

data.

Writers

(setf data).

Slot: %indexes
Initargs

:indexes

Readers

indexes.

Writers

(setf indexes).

Class: parameters
Package

clusters.

Source

types.lisp.

Direct subclasses
Direct methods
Direct Default Initargs
InitargValue
:key-function(function identity)
:parallelpnil
:silhouette-sample-count15
:silhouette-sample-size500
Direct slots
Slot: %parallelp
Initargs

:parallelp

Readers

parallelp.

Writers

This slot is read-only.

Slot: %key-function
Initargs

:key-function

Readers

key-function.

Writers

This slot is read-only.

Slot: %silhouette-sample-count
Initargs

:silhouette-sample-count

Readers

silhouette-sample-count.

Writers

This slot is read-only.

Slot: %silhouette-sample-size
Initargs

:silhouette-sample-size

Readers

silhouette-sample-size.

Writers

This slot is read-only.

Class: parameters
Package

clusters.pam.

Source

types.lisp.

Direct superclasses

parameters.

Direct methods
Direct Default Initargs
InitargValue
:split-thresholdnil
:merge-thresholdnil
:select-medoids-attempts-count20
:split-merge-attempts-count0
Direct slots
Slot: %split-threshold
Initargs

:split-threshold

Readers
Writers

(setf split-threshold).

Slot: %merge-threshold
Initargs

:merge-threshold

Readers
Writers

(setf merge-threshold).

Slot: %select-medoids-attempts-count
Initargs

:select-medoids-attempts-count

Readers
Writers

(setf select-medoids-attempts-count).

Slot: %split-merge-attempts-count
Initargs

:split-merge-attempts-count

Readers
Writers

(setf split-merge-attempts-count).

Slot: %medoids-count
Initargs

:medoids-count

Readers
Writers

(setf medoids-count).

Class: parameters
Package

clusters.clarans.

Source

types.lisp.

Direct superclasses

parameters.

Direct methods
Direct slots
Slot: %distance-function
Initargs

:distance-function

Readers
Writers

(setf distance-function).

Slot: %max-neighbor
Initargs

:max-neighbor

Readers

max-neighbor.

Writers

(setf max-neighbor).

Slot: %medoids-count
Initargs

:medoids-count

Readers

medoids-count.

Writers

(setf medoids-count).

Class: parameters
Package

clusters.k-means.

Source

types.lisp.

Direct superclasses

parameters.

Direct methods
Direct Default Initargs
InitargValue
:iterationsnil
Direct slots
Slot: %medoids-count
Type

alexandria:non-negative-fixnum

Initargs

:medoids-count

Readers
Writers

(setf medoids-count).

Slot: %iterations
Initargs

:iterations

Readers
Writers

(setf iterations).

Slot: %distortion-epsilon
Type

single-float

Initargs

:distortion-epsilon

Readers
Writers

(setf distortion-epsilon).

Class: result
Package

clusters.

Source

types.lisp.

Direct superclasses

parameters-holder.

Direct subclasses

pam-result.

Direct methods
Direct slots
Slot: %cluster-indexes
Type

vector

Initargs

:cluster-indexes

Readers

cluster-indexes.

Writers

This slot is read-only.

Slot: %indexes
Initargs

:indexes

Readers

indexes.

Writers

This slot is read-only.

Slot: %data
Type

vector

Initargs

:data

Readers

data.

Writers

This slot is read-only.

Slot: %silhouette
Type

(vector single-float)

Initargs

:silhouette

Readers

silhouette.

Writers

This slot is read-only.


6.2 Internals


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6.2.1 Constants

Constant: +sqrt2+
Package

clusters.metric.

Source

hellinger.lisp.


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6.2.2 Macros

Macro: with-grid-mapping-resources (max-length (&key g1 g2 g3 to-sum) &body body)
Package

clusters.metric.

Source

svr.lisp.


Next: , Previous: , Up: Internals   [Contents][Index]

6.2.3 Ordinary functions

Function: array-sum (iteration sum-size to-sum grid)
Package

clusters.metric.

Source

svr.lisp.

Function: assign-data-points-to-medoids (state)
Package

clusters.k-means.

Source

utils.lisp.

Function: average-distance-to-element (distance-matrix element cluster)
Package

clusters.

Source

silhouette.lisp.

Function: build-clusters (state &optional split-merge)
Package

clusters.pam.

Source

utils.lisp.

Function: choose-effective-medoid (state cluster)
Package

clusters.pam.

Source

utils.lisp.

Function: choose-effective-medoids (state)
Package

clusters.pam.

Source

utils.lisp.

Function: choose-initial-medoids (state)
Package

clusters.pam.

Source

utils.lisp.

Function: clear-cluster-contents (state)
Package

clusters.pam.

Source

utils.lisp.

Function: clear-unfinished-clusters (state)
Package

clusters.pam.

Source

utils.lisp.

Function: closest-medoid (state index)
Package

clusters.pam.

Source

utils.lisp.

Function: cluster-values (data index-vector)
Package

clusters.

Source

utils.lisp.

Function: column-index (k i n)
Package

clusters.utils.

Source

matrix.lisp.

Function: contains (medoids medoid)
Package

clusters.clarans.

Source

utils.lisp.

Function: count->half-matrix-size (count)
Package

clusters.utils.

Source

matrix.lisp.

Function: count-of-all-possible-subvectors-upto-length (length-of-vector length-of-subvector &optional buffer)
Package

clusters.metric.

Source

svr.lisp.

Function: distance-matrix (result &optional indexes)
Package

clusters.

Source

silhouette.lisp.

Function: distortion (state)
Package

clusters.k-means.

Source

utils.lisp.

Function: earth-mover-metric (a b)
Package

clusters.metric.

Source

earth-mover.lisp.

Function: element-in-i-rows (i n)
Package

clusters.utils.

Source

matrix.lisp.

Function: fill-reclustering-index-vector (state indexes count-of-eliminated)
Package

clusters.pam.

Source

utils.lisp.

Function: grid-mapping (first-sequence second-sequence &optional grid first-grid prev-grid to-sum)
Package

clusters.metric.

Source

svr.lisp.

Function: inter-cluster-distances (distance-matrix cluster sample)
Package

clusters.

Source

silhouette.lisp.

Function: intra-cluster-distances (distance-matrix cluster)
Package

clusters.

Source

silhouette.lisp.

Function: max-condition (u sum-row n epsilon)
Package

clusters.distance.

Source

sinkhorn.lisp.

Function: medoidp (state index)
Package

clusters.pam.

Source

utils.lisp.

Function: order-medoids (state)
Package

clusters.pam.

Source

utils.lisp.

Function: prepare-reclustering-index-vector (state)
Package

clusters.pam.

Source

utils.lisp.

Function: random-medoid (n medoids)
Package

clusters.clarans.

Source

utils.lisp.

Function: random-neighbor (parallelp data indexes medoids y d distance-function)
Package

clusters.clarans.

Source

utils.lisp.

Function: recluster-clusters-of-invalid-size (state)
Package

clusters.pam.

Source

utils.lisp.

Function: reset (object)
Package

clusters.pam.

Source

utils.lisp.

Function: row-index (k n)
Package

clusters.utils.

Source

matrix.lisp.

Function: same-events (grid sequence-a sequence-b to-sum)
Package

clusters.metric.

Source

svr.lisp.

Function: scan-for-clusters-of-invalid-size (state)
Package

clusters.pam.

Source

utils.lisp.

Function: select-initial-medoids (state)
Package

clusters.k-means.

Source

utils.lisp.

Function: select-new-medoids (state)
Package

clusters.k-means.

Source

utils.lisp.

Function: select-random-cluster-subsets (result distance-matrix-supplied)
Package

clusters.

Source

silhouette.lisp.

Function: sinkhorn-optimal-transport-matrix (cost vector-1 vector-2 regularization-strength epsilon)
Package

clusters.distance.

Source

sinkhorn.lisp.

Function: sum-row (u transport-matrix n m)
Package

clusters.distance.

Source

sinkhorn.lisp.

Function: to-cluster-contents (y indexes medoids-counts)
Package

clusters.clarans.

Source

utils.lisp.

Function: unfinished-clusters-p (state)
Package

clusters.pam.

Source

utils.lisp.

Function: update-grid (a-length b-length sum-size to-sum grid prev-grid iteration)
Package

clusters.metric.

Source

svr.lisp.


Next: , Previous: , Up: Internals   [Contents][Index]

6.2.4 Generic functions

Generic Reader: access-cluster-contents (object)
Package

clusters.pam.

Methods
Reader Method: access-cluster-contents ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%cluster-contents.

Generic Writer: (setf access-cluster-contents) (object)
Package

clusters.pam.

Methods
Writer Method: (setf access-cluster-contents) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%cluster-contents.

Generic Reader: access-cluster-size (object)
Package

clusters.pam.

Methods
Reader Method: access-cluster-size ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%cluster-size.

Generic Writer: (setf access-cluster-size) (object)
Package

clusters.pam.

Methods
Writer Method: (setf access-cluster-size) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%cluster-size.

Generic Reader: access-distance-matrix (object)
Package

clusters.pam.

Methods
Reader Method: access-distance-matrix ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%distance-matrix.

Generic Writer: (setf access-distance-matrix) (object)
Package

clusters.pam.

Methods
Writer Method: (setf access-distance-matrix) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%distance-matrix.

Generic Reader: access-medoids (object)
Package

clusters.k-means.

Methods
Reader Method: access-medoids ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%medoids.

Generic Writer: (setf access-medoids) (object)
Package

clusters.k-means.

Methods
Writer Method: (setf access-medoids) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%medoids.

Generic Reader: access-medoids-count (object)
Package

clusters.pam.

Methods
Reader Method: access-medoids-count ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Writer: (setf access-medoids-count) (object)
Package

clusters.pam.

Methods
Writer Method: (setf access-medoids-count) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Reader: access-unfinished-clusters (object)
Package

clusters.pam.

Methods
Reader Method: access-unfinished-clusters ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%unfinished-clusters.

Generic Writer: (setf access-unfinished-clusters) (object)
Package

clusters.pam.

Methods
Writer Method: (setf access-unfinished-clusters) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%unfinished-clusters.

Generic Function: assign-data-points-to-medoids (state)
Package

clusters.pam.

Methods
Method: assign-data-points-to-medoids (state)
Source

utils.lisp.

Generic Reader: d (state)
Package

clusters.clarans.

Source

generics.lisp.

Methods
Reader Method: d ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%d.

Generic Writer: (setf d) (state)
Package

clusters.clarans.

Source

generics.lisp.

Methods
Writer Method: (setf d) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%d.

Generic Reader: distance-function (object)
Package

clusters.clarans.

Methods
Reader Method: distance-function ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%distance-function.

Generic Writer: (setf distance-function) (object)
Package

clusters.clarans.

Methods
Writer Method: (setf distance-function) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%distance-function.

Generic Reader: distortion (state)
Package

clusters.clarans.

Source

generics.lisp.

Methods
Reader Method: distortion ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%distortion.

Generic Writer: (setf distortion) (state)
Package

clusters.clarans.

Source

generics.lisp.

Methods
Writer Method: (setf distortion) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%distortion.

Generic Reader: distortion-epsilon (object)
Package

clusters.k-means.

Methods
Reader Method: distortion-epsilon ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%distortion-epsilon.

Generic Writer: (setf distortion-epsilon) (object)
Package

clusters.k-means.

Methods
Writer Method: (setf distortion-epsilon) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%distortion-epsilon.

Generic Reader: iterations (object)
Package

clusters.k-means.

Methods
Reader Method: iterations ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%iterations.

Generic Writer: (setf iterations) (object)
Package

clusters.k-means.

Methods
Writer Method: (setf iterations) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%iterations.

Generic Function: max-neighbor (object)
Package

clusters.clarans.

Methods
Method: max-neighbor ((state algorithm-state))
Source

methods.lisp.

Reader Method: max-neighbor ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%max-neighbor.

Generic Writer: (setf max-neighbor) (object)
Package

clusters.clarans.

Methods
Writer Method: (setf max-neighbor) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%max-neighbor.

Generic Reader: medoids (state)
Package

clusters.clarans.

Source

generics.lisp.

Methods
Reader Method: medoids ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%medoids.

Generic Writer: (setf medoids) (state)
Package

clusters.clarans.

Source

generics.lisp.

Methods
Writer Method: (setf medoids) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%medoids.

Generic Reader: medoids-count (object)
Package

clusters.pam.

Methods
Reader Method: medoids-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Writer: (setf medoids-count) (object)
Package

clusters.pam.

Methods
Writer Method: (setf medoids-count) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Function: medoids-count (object)
Package

clusters.clarans.

Methods
Method: medoids-count ((state algorithm-state))
Source

methods.lisp.

Reader Method: medoids-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Writer: (setf medoids-count) (object)
Package

clusters.clarans.

Methods
Writer Method: (setf medoids-count) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Reader: medoids-count (object)
Package

clusters.k-means.

Methods
Reader Method: medoids-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Writer: (setf medoids-count) (object)
Package

clusters.k-means.

Methods
Writer Method: (setf medoids-count) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Reader: merge-threshold (object)
Package

clusters.pam.

Methods
Reader Method: merge-threshold ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%merge-threshold.

Generic Writer: (setf merge-threshold) (object)
Package

clusters.pam.

Methods
Writer Method: (setf merge-threshold) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%merge-threshold.

Generic Function: parallel-p (parameters)
Package

clusters.

Source

generics.lisp.

Generic Reader: read-clusters (object)
Package

clusters.k-means.

Methods
Reader Method: read-clusters ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%clusters.

Generic Reader: read-distance-matrix (object)
Package

clusters.pam.

Methods
Reader Method: read-distance-matrix ((pam-result pam-result))

automatically generated reader method

Source

types.lisp.

Target Slot

%distance-matrix.

Generic Function: read-distortion-epsilon (object)
Package

clusters.k-means.

Methods
Method: read-distortion-epsilon ((state algorithm-state))
Source

methods.lisp.

Reader Method: read-distortion-epsilon ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%distortion-epsilon.

Generic Function: read-iterations (object)
Package

clusters.k-means.

Methods
Method: read-iterations ((state algorithm-state))
Source

methods.lisp.

Reader Method: read-iterations ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%iterations.

Generic Reader: read-medoids-count (object)
Package

clusters.pam.

Methods
Reader Method: read-medoids-count ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%medoids-count.

Reader Method: read-medoids-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Function: read-medoids-count (object)
Package

clusters.k-means.

Methods
Method: read-medoids-count ((state algorithm-state))
Source

methods.lisp.

Reader Method: read-medoids-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%medoids-count.

Generic Function: read-merge-threshold (object)
Package

clusters.pam.

Methods
Method: read-merge-threshold ((algorithm-state algorithm-state))
Source

methods.lisp.

Reader Method: read-merge-threshold ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%merge-threshold.

Generic Function: read-select-medoids-attempts-count (object)
Package

clusters.pam.

Methods
Method: read-select-medoids-attempts-count ((algorithm-state algorithm-state))
Source

methods.lisp.

Reader Method: read-select-medoids-attempts-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%select-medoids-attempts-count.

Generic Function: read-split-merge-attempts-count (object)
Package

clusters.pam.

Methods
Method: read-split-merge-attempts-count ((algorithm-state algorithm-state))
Source

methods.lisp.

Reader Method: read-split-merge-attempts-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%split-merge-attempts-count.

Generic Function: read-split-threshold (object)
Package

clusters.pam.

Methods
Method: read-split-threshold ((algorithm-state algorithm-state))
Source

methods.lisp.

Reader Method: read-split-threshold ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%split-threshold.

Generic Reader: select-medoids-attempts-count (object)
Package

clusters.pam.

Methods
Reader Method: select-medoids-attempts-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%select-medoids-attempts-count.

Generic Writer: (setf select-medoids-attempts-count) (object)
Package

clusters.pam.

Methods
Writer Method: (setf select-medoids-attempts-count) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%select-medoids-attempts-count.

Generic Reader: split-merge-attempts-count (object)
Package

clusters.pam.

Methods
Reader Method: split-merge-attempts-count ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%split-merge-attempts-count.

Generic Writer: (setf split-merge-attempts-count) (object)
Package

clusters.pam.

Methods
Writer Method: (setf split-merge-attempts-count) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%split-merge-attempts-count.

Generic Reader: split-threshold (object)
Package

clusters.pam.

Methods
Reader Method: split-threshold ((parameters parameters))

automatically generated reader method

Source

types.lisp.

Target Slot

%split-threshold.

Generic Writer: (setf split-threshold) (object)
Package

clusters.pam.

Methods
Writer Method: (setf split-threshold) ((parameters parameters))

automatically generated writer method

Source

types.lisp.

Target Slot

%split-threshold.

Generic Reader: y (state)
Package

clusters.clarans.

Source

generics.lisp.

Methods
Reader Method: y ((algorithm-state algorithm-state))

automatically generated reader method

Source

types.lisp.

Target Slot

%y.

Generic Writer: (setf y) (state)
Package

clusters.clarans.

Source

generics.lisp.

Methods
Writer Method: (setf y) ((algorithm-state algorithm-state))

automatically generated writer method

Source

types.lisp.

Target Slot

%y.


Next: , Previous: , Up: Internals   [Contents][Index]

6.2.5 Classes

Class: algorithm-state
Package

clusters.pam.

Source

types.lisp.

Direct superclasses

algorithm-state.

Direct methods
Direct Default Initargs
InitargValue
:cluster-contentsnil
:medoids-countnil
:cluster-sizenil
:distance-matrixnil
:unfinished-clustersnil
Direct slots
Slot: %cluster-contents
Initargs

:cluster-contents

Readers

access-cluster-contents.

Writers

(setf access-cluster-contents).

Slot: %medoids-count
Initargs

:medoids-count

Readers
Writers

(setf access-medoids-count).

Slot: %unfinished-clusters
Initargs

:unfinished-clusters

Readers

access-unfinished-clusters.

Writers

(setf access-unfinished-clusters).

Slot: %distance-matrix
Initargs

:distance-matrix

Readers

access-distance-matrix.

Writers

(setf access-distance-matrix).

Slot: %cluster-size
Initargs

:cluster-size

Readers

access-cluster-size.

Writers

(setf access-cluster-size).

Class: algorithm-state
Package

clusters.clarans.

Source

types.lisp.

Direct superclasses

algorithm-state.

Direct methods
Direct Default Initargs
InitargValue
:ynil
:medoidsnil
:distortionnil
:dnil
Direct slots
Slot: %y
Initargs

:y

Readers

y.

Writers

(setf y).

Slot: %medoids
Initargs

:medoids

Readers

medoids.

Writers

(setf medoids).

Slot: %distortion
Initargs

:distortion

Readers

distortion.

Writers

(setf distortion).

Slot: %d
Initargs

:d

Readers

d.

Writers

(setf d).

Class: algorithm-state
Package

clusters.k-means.

Source

types.lisp.

Direct superclasses

algorithm-state.

Direct methods
Direct Default Initargs
InitargValue
:clusters(vect)
:medoids(vect)
Direct slots
Slot: %clusters
Type

vector

Initargs

:clusters

Readers

read-clusters.

Writers

This slot is read-only.

Slot: %medoids
Type

vector

Initargs

:medoids

Readers

access-medoids.

Writers

(setf access-medoids).

Class: pam-result
Package

clusters.pam.

Source

types.lisp.

Direct superclasses

result.

Direct methods

read-distance-matrix.

Direct slots
Slot: %distance-matrix
Initargs

:distance-matrix

Readers

read-distance-matrix.

Writers

This slot is read-only.

Class: parameters-holder
Package

clusters.

Source

types.lisp.

Direct subclasses
Direct methods
Direct slots
Slot: %parameters
Initargs

:parameters

Readers

parameters.

Writers

This slot is read-only.


Previous: , Up: Internals   [Contents][Index]

6.2.6 Types

Type: index-array ()
Package

clusters.clarans.

Source

types.lisp.


Appendix A Indexes


Next: , Previous: , Up: Indexes   [Contents][Index]

A.1 Concepts


Next: , Previous: , Up: Indexes   [Contents][Index]

A.2 Functions

Jump to:   (  
A   B   C   D   E   F   G   H   I   K   L   M   O   P   R   S   T   U   W   Y  
Index Entry  Section

(
(setf access-cluster-contents): Private generic functions
(setf access-cluster-contents): Private generic functions
(setf access-cluster-size): Private generic functions
(setf access-cluster-size): Private generic functions
(setf access-distance-matrix): Private generic functions
(setf access-distance-matrix): Private generic functions
(setf access-medoids): Private generic functions
(setf access-medoids): Private generic functions
(setf access-medoids-count): Private generic functions
(setf access-medoids-count): Private generic functions
(setf access-unfinished-clusters): Private generic functions
(setf access-unfinished-clusters): Private generic functions
(setf d): Private generic functions
(setf d): Private generic functions
(setf data): Public generic functions
(setf data): Public generic functions
(setf distance-function): Private generic functions
(setf distance-function): Private generic functions
(setf distortion): Private generic functions
(setf distortion): Private generic functions
(setf distortion-epsilon): Private generic functions
(setf distortion-epsilon): Private generic functions
(setf indexes): Public generic functions
(setf indexes): Public generic functions
(setf iterations): Private generic functions
(setf iterations): Private generic functions
(setf max-neighbor): Private generic functions
(setf max-neighbor): Private generic functions
(setf medoids): Private generic functions
(setf medoids): Private generic functions
(setf medoids-count): Private generic functions
(setf medoids-count): Private generic functions
(setf medoids-count): Private generic functions
(setf medoids-count): Private generic functions
(setf medoids-count): Private generic functions
(setf medoids-count): Private generic functions
(setf merge-threshold): Private generic functions
(setf merge-threshold): Private generic functions
(setf mref): Public ordinary functions
(setf select-medoids-attempts-count): Private generic functions
(setf select-medoids-attempts-count): Private generic functions
(setf split-merge-attempts-count): Private generic functions
(setf split-merge-attempts-count): Private generic functions
(setf split-threshold): Private generic functions
(setf split-threshold): Private generic functions
(setf y): Private generic functions
(setf y): Private generic functions

A
access-cluster-contents: Private generic functions
access-cluster-contents: Private generic functions
access-cluster-size: Private generic functions
access-cluster-size: Private generic functions
access-distance-matrix: Private generic functions
access-distance-matrix: Private generic functions
access-medoids: Private generic functions
access-medoids: Private generic functions
access-medoids-count: Private generic functions
access-medoids-count: Private generic functions
access-unfinished-clusters: Private generic functions
access-unfinished-clusters: Private generic functions
algorithm-state-class: Public generic functions
algorithm-state-class: Public generic functions
algorithm-state-class: Public generic functions
algorithm-state-class: Public generic functions
algorithm-state-initialization-list: Public generic functions
algorithm-state-initialization-list: Public generic functions
algorithm-state-initialization-list: Public generic functions
algorithm-state-initialization-list: Public generic functions
array-sum: Private ordinary functions
assign-data-points-to-medoids: Private ordinary functions
assign-data-points-to-medoids: Private generic functions
assign-data-points-to-medoids: Private generic functions
average: Public ordinary functions
average-distance-to-element: Private ordinary functions

B
bhattacharyya: Public ordinary functions
build-clusters: Private ordinary functions

C
calculate-silhouette: Public ordinary functions
calculate-silhouette*: Public generic functions
calculate-silhouette*: Public generic functions
calculate-silhouette*: Public generic functions
choose-effective-medoid: Private ordinary functions
choose-effective-medoids: Private ordinary functions
choose-initial-medoids: Private ordinary functions
clear-cluster-contents: Private ordinary functions
clear-unfinished-clusters: Private ordinary functions
closest-medoid: Private ordinary functions
cluster: Public ordinary functions
cluster-contents: Public generic functions
cluster-contents: Public generic functions
cluster-indexes: Public generic functions
cluster-indexes: Public generic functions
cluster-values: Private ordinary functions
column-index: Private ordinary functions
contains: Private ordinary functions
copy-into: Public ordinary functions
count->half-matrix-size: Private ordinary functions
count-of-all-possible-subvectors-upto-length: Private ordinary functions

D
d: Private generic functions
d: Private generic functions
data: Public generic functions
data: Public generic functions
data: Public generic functions
defpackage: Public macros
distance-function: Public generic functions
distance-function: Public generic functions
distance-function: Public generic functions
distance-function: Public generic functions
distance-function: Private generic functions
distance-function: Private generic functions
distance-matrix: Public ordinary functions
distance-matrix: Private ordinary functions
distortion: Private ordinary functions
distortion: Private generic functions
distortion: Private generic functions
distortion-epsilon: Private generic functions
distortion-epsilon: Private generic functions
draw-random-vector: Public ordinary functions

E
earth-mover-metric: Private ordinary functions
element-in-i-rows: Private ordinary functions
euclid: Public ordinary functions

F
fill-reclustering-index-vector: Private ordinary functions
Function, (setf mref): Public ordinary functions
Function, array-sum: Private ordinary functions
Function, assign-data-points-to-medoids: Private ordinary functions
Function, average: Public ordinary functions
Function, average-distance-to-element: Private ordinary functions
Function, bhattacharyya: Public ordinary functions
Function, build-clusters: Private ordinary functions
Function, calculate-silhouette: Public ordinary functions
Function, choose-effective-medoid: Private ordinary functions
Function, choose-effective-medoids: Private ordinary functions
Function, choose-initial-medoids: Private ordinary functions
Function, clear-cluster-contents: Private ordinary functions
Function, clear-unfinished-clusters: Private ordinary functions
Function, closest-medoid: Private ordinary functions
Function, cluster: Public ordinary functions
Function, cluster-values: Private ordinary functions
Function, column-index: Private ordinary functions
Function, contains: Private ordinary functions
Function, copy-into: Public ordinary functions
Function, count->half-matrix-size: Private ordinary functions
Function, count-of-all-possible-subvectors-upto-length: Private ordinary functions
Function, distance-matrix: Public ordinary functions
Function, distance-matrix: Private ordinary functions
Function, distortion: Private ordinary functions
Function, draw-random-vector: Public ordinary functions
Function, earth-mover-metric: Private ordinary functions
Function, element-in-i-rows: Private ordinary functions
Function, euclid: Public ordinary functions
Function, fill-reclustering-index-vector: Private ordinary functions
Function, grid-mapping: Private ordinary functions
Function, group-average: Public ordinary functions
Function, half-matrix-index->square-row/column: Public ordinary functions
Function, half-matrix-size->count: Public ordinary functions
Function, hausdorff: Public ordinary functions
Function, hellinger: Public ordinary functions
Function, inter-cluster-distances: Private ordinary functions
Function, intra-cluster-distances: Private ordinary functions
Function, lazy-shuffle: Public ordinary functions
Function, lcs: Public ordinary functions
Function, levenshtein: Public ordinary functions
Function, make-algorithm-state: Public ordinary functions
Function, make-half-matrix: Public ordinary functions
Function, map-into-half-matrix: Public ordinary functions
Function, max-condition: Private ordinary functions
Function, medoidp: Private ordinary functions
Function, mref: Public ordinary functions
Function, obtain-result: Public ordinary functions
Function, order-medoids: Private ordinary functions
Function, pmap: Public ordinary functions
Function, pmap-into: Public ordinary functions
Function, prepare-reclustering-index-vector: Private ordinary functions
Function, random-medoid: Private ordinary functions
Function, random-neighbor: Private ordinary functions
Function, recluster-clusters-of-invalid-size: Private ordinary functions
Function, reset: Private ordinary functions
Function, row-index: Private ordinary functions
Function, same-events: Private ordinary functions
Function, scan-for-clusters-of-invalid-size: Private ordinary functions
Function, seed: Public ordinary functions
Function, select-initial-medoids: Private ordinary functions
Function, select-new-medoids: Private ordinary functions
Function, select-random-cluster-subsets: Private ordinary functions
Function, sinkhorn: Public ordinary functions
Function, sinkhorn-optimal-transport-matrix: Private ordinary functions
Function, square-row/column->half-matrix-index: Public ordinary functions
Function, sum-row: Private ordinary functions
Function, svr: Public ordinary functions
Function, swap-if: Public ordinary functions
Function, to-cluster-contents: Private ordinary functions
Function, transform: Public ordinary functions
Function, unfinished-clusters-p: Private ordinary functions
Function, update-grid: Private ordinary functions

G
Generic Function, (setf access-cluster-contents): Private generic functions
Generic Function, (setf access-cluster-size): Private generic functions
Generic Function, (setf access-distance-matrix): Private generic functions
Generic Function, (setf access-medoids): Private generic functions
Generic Function, (setf access-medoids-count): Private generic functions
Generic Function, (setf access-unfinished-clusters): Private generic functions
Generic Function, (setf d): Private generic functions
Generic Function, (setf data): Public generic functions
Generic Function, (setf distance-function): Private generic functions
Generic Function, (setf distortion): Private generic functions
Generic Function, (setf distortion-epsilon): Private generic functions
Generic Function, (setf indexes): Public generic functions
Generic Function, (setf iterations): Private generic functions
Generic Function, (setf max-neighbor): Private generic functions
Generic Function, (setf medoids): Private generic functions
Generic Function, (setf medoids-count): Private generic functions
Generic Function, (setf medoids-count): Private generic functions
Generic Function, (setf medoids-count): Private generic functions
Generic Function, (setf merge-threshold): Private generic functions
Generic Function, (setf select-medoids-attempts-count): Private generic functions
Generic Function, (setf split-merge-attempts-count): Private generic functions
Generic Function, (setf split-threshold): Private generic functions
Generic Function, (setf y): Private generic functions
Generic Function, access-cluster-contents: Private generic functions
Generic Function, access-cluster-size: Private generic functions
Generic Function, access-distance-matrix: Private generic functions
Generic Function, access-medoids: Private generic functions
Generic Function, access-medoids-count: Private generic functions
Generic Function, access-unfinished-clusters: Private generic functions
Generic Function, algorithm-state-class: Public generic functions
Generic Function, algorithm-state-initialization-list: Public generic functions
Generic Function, assign-data-points-to-medoids: Private generic functions
Generic Function, calculate-silhouette*: Public generic functions
Generic Function, cluster-contents: Public generic functions
Generic Function, cluster-indexes: Public generic functions
Generic Function, d: Private generic functions
Generic Function, data: Public generic functions
Generic Function, distance-function: Public generic functions
Generic Function, distance-function: Private generic functions
Generic Function, distortion: Private generic functions
Generic Function, distortion-epsilon: Private generic functions
Generic Function, indexes: Public generic functions
Generic Function, iterations: Private generic functions
Generic Function, key-function: Public generic functions
Generic Function, max-neighbor: Private generic functions
Generic Function, medoids: Private generic functions
Generic Function, medoids-count: Private generic functions
Generic Function, medoids-count: Private generic functions
Generic Function, medoids-count: Private generic functions
Generic Function, merge-threshold: Private generic functions
Generic Function, parallel-p: Private generic functions
Generic Function, parallelp: Public generic functions
Generic Function, parameters: Public generic functions
Generic Function, read-clusters: Private generic functions
Generic Function, read-distance-matrix: Private generic functions
Generic Function, read-distortion-epsilon: Private generic functions
Generic Function, read-iterations: Private generic functions
Generic Function, read-medoids-count: Private generic functions
Generic Function, read-medoids-count: Private generic functions
Generic Function, read-merge-threshold: Private generic functions
Generic Function, read-select-medoids-attempts-count: Private generic functions
Generic Function, read-split-merge-attempts-count: Private generic functions
Generic Function, read-split-threshold: Private generic functions
Generic Function, result-class: Public generic functions
Generic Function, result-initialization-list: Public generic functions
Generic Function, run-algorithm: Public generic functions
Generic Function, select-medoids-attempts-count: Private generic functions
Generic Function, silhouette: Public generic functions
Generic Function, silhouette-sample-count: Public generic functions
Generic Function, silhouette-sample-size: Public generic functions
Generic Function, split-merge-attempts-count: Private generic functions
Generic Function, split-threshold: Private generic functions
Generic Function, y: Private generic functions
grid-mapping: Private ordinary functions
group-average: Public ordinary functions

H
half-matrix-index->square-row/column: Public ordinary functions
half-matrix-size->count: Public ordinary functions
hausdorff: Public ordinary functions
hellinger: Public ordinary functions

I
indexes: Public generic functions
indexes: Public generic functions
indexes: Public generic functions
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
initialize-instance: Public standalone methods
inter-cluster-distances: Private ordinary functions
intra-cluster-distances: Private ordinary functions
iterations: Private generic functions
iterations: Private generic functions

K
key-function: Public generic functions
key-function: Public generic functions
key-function: Public generic functions

L
lazy-shuffle: Public ordinary functions
lcs: Public ordinary functions
levenshtein: Public ordinary functions

M
Macro, defpackage: Public macros
Macro, with-grid-mapping-resources: Private macros
make-algorithm-state: Public ordinary functions
make-half-matrix: Public ordinary functions
map-into-half-matrix: Public ordinary functions
max-condition: Private ordinary functions
max-neighbor: Private generic functions
max-neighbor: Private generic functions
max-neighbor: Private generic functions
medoidp: Private ordinary functions
medoids: Private generic functions
medoids: Private generic functions
medoids-count: Private generic functions
medoids-count: Private generic functions
medoids-count: Private generic functions
medoids-count: Private generic functions
medoids-count: Private generic functions
medoids-count: Private generic functions
medoids-count: Private generic functions
merge-threshold: Private generic functions
merge-threshold: Private generic functions
Method, (setf access-cluster-contents): Private generic functions
Method, (setf access-cluster-size): Private generic functions
Method, (setf access-distance-matrix): Private generic functions
Method, (setf access-medoids): Private generic functions
Method, (setf access-medoids-count): Private generic functions
Method, (setf access-unfinished-clusters): Private generic functions
Method, (setf d): Private generic functions
Method, (setf data): Public generic functions
Method, (setf distance-function): Private generic functions
Method, (setf distortion): Private generic functions
Method, (setf distortion-epsilon): Private generic functions
Method, (setf indexes): Public generic functions
Method, (setf iterations): Private generic functions
Method, (setf max-neighbor): Private generic functions
Method, (setf medoids): Private generic functions
Method, (setf medoids-count): Private generic functions
Method, (setf medoids-count): Private generic functions
Method, (setf medoids-count): Private generic functions
Method, (setf merge-threshold): Private generic functions
Method, (setf select-medoids-attempts-count): Private generic functions
Method, (setf split-merge-attempts-count): Private generic functions
Method, (setf split-threshold): Private generic functions
Method, (setf y): Private generic functions
Method, access-cluster-contents: Private generic functions
Method, access-cluster-size: Private generic functions
Method, access-distance-matrix: Private generic functions
Method, access-medoids: Private generic functions
Method, access-medoids-count: Private generic functions
Method, access-unfinished-clusters: Private generic functions
Method, algorithm-state-class: Public generic functions
Method, algorithm-state-class: Public generic functions
Method, algorithm-state-class: Public generic functions
Method, algorithm-state-initialization-list: Public generic functions
Method, algorithm-state-initialization-list: Public generic functions
Method, algorithm-state-initialization-list: Public generic functions
Method, assign-data-points-to-medoids: Private generic functions
Method, calculate-silhouette*: Public generic functions
Method, calculate-silhouette*: Public generic functions
Method, cluster-contents: Public generic functions
Method, cluster-indexes: Public generic functions
Method, d: Private generic functions
Method, data: Public generic functions
Method, data: Public generic functions
Method, distance-function: Public generic functions
Method, distance-function: Public generic functions
Method, distance-function: Public generic functions
Method, distance-function: Private generic functions
Method, distortion: Private generic functions
Method, distortion-epsilon: Private generic functions
Method, indexes: Public generic functions
Method, indexes: Public generic functions
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, initialize-instance: Public standalone methods
Method, iterations: Private generic functions
Method, key-function: Public generic functions
Method, key-function: Public generic functions
Method, max-neighbor: Private generic functions
Method, max-neighbor: Private generic functions
Method, medoids: Private generic functions
Method, medoids-count: Private generic functions
Method, medoids-count: Private generic functions
Method, medoids-count: Private generic functions
Method, medoids-count: Private generic functions
Method, merge-threshold: Private generic functions
Method, parallelp: Public generic functions
Method, parallelp: Public generic functions
Method, parameters: Public generic functions
Method, read-clusters: Private generic functions
Method, read-distance-matrix: Private generic functions
Method, read-distortion-epsilon: Private generic functions
Method, read-distortion-epsilon: Private generic functions
Method, read-iterations: Private generic functions
Method, read-iterations: Private generic functions
Method, read-medoids-count: Private generic functions
Method, read-medoids-count: Private generic functions
Method, read-medoids-count: Private generic functions
Method, read-medoids-count: Private generic functions
Method, read-merge-threshold: Private generic functions
Method, read-merge-threshold: Private generic functions
Method, read-select-medoids-attempts-count: Private generic functions
Method, read-select-medoids-attempts-count: Private generic functions
Method, read-split-merge-attempts-count: Private generic functions
Method, read-split-merge-attempts-count: Private generic functions
Method, read-split-threshold: Private generic functions
Method, read-split-threshold: Private generic functions
Method, result-class: Public generic functions
Method, result-class: Public generic functions
Method, result-class: Public generic functions
Method, result-initialization-list: Public generic functions
Method, result-initialization-list: Public generic functions
Method, result-initialization-list: Public generic functions
Method, result-initialization-list: Public generic functions
Method, run-algorithm: Public generic functions
Method, run-algorithm: Public generic functions
Method, run-algorithm: Public generic functions
Method, select-medoids-attempts-count: Private generic functions
Method, silhouette: Public generic functions
Method, silhouette: Public generic functions
Method, silhouette-sample-count: Public generic functions
Method, silhouette-sample-count: Public generic functions
Method, silhouette-sample-size: Public generic functions
Method, silhouette-sample-size: Public generic functions
Method, split-merge-attempts-count: Private generic functions
Method, split-threshold: Private generic functions
Method, y: Private generic functions
mref: Public ordinary functions

O
obtain-result: Public ordinary functions
order-medoids: Private ordinary functions

P
parallel-p: Private generic functions
parallelp: Public generic functions
parallelp: Public generic functions
parallelp: Public generic functions
parameters: Public generic functions
parameters: Public generic functions
pmap: Public ordinary functions
pmap-into: Public ordinary functions
prepare-reclustering-index-vector: Private ordinary functions

R
random-medoid: Private ordinary functions
random-neighbor: Private ordinary functions
read-clusters: Private generic functions
read-clusters: Private generic functions
read-distance-matrix: Private generic functions
read-distance-matrix: Private generic functions
read-distortion-epsilon: Private generic functions
read-distortion-epsilon: Private generic functions
read-distortion-epsilon: Private generic functions
read-iterations: Private generic functions
read-iterations: Private generic functions
read-iterations: Private generic functions
read-medoids-count: Private generic functions
read-medoids-count: Private generic functions
read-medoids-count: Private generic functions
read-medoids-count: Private generic functions
read-medoids-count: Private generic functions
read-medoids-count: Private generic functions
read-merge-threshold: Private generic functions
read-merge-threshold: Private generic functions
read-merge-threshold: Private generic functions
read-select-medoids-attempts-count: Private generic functions
read-select-medoids-attempts-count: Private generic functions
read-select-medoids-attempts-count: Private generic functions
read-split-merge-attempts-count: Private generic functions
read-split-merge-attempts-count: Private generic functions
read-split-merge-attempts-count: Private generic functions
read-split-threshold: Private generic functions
read-split-threshold: Private generic functions
read-split-threshold: Private generic functions
recluster-clusters-of-invalid-size: Private ordinary functions
reset: Private ordinary functions
result-class: Public generic functions
result-class: Public generic functions
result-class: Public generic functions
result-class: Public generic functions
result-initialization-list: Public generic functions
result-initialization-list: Public generic functions
result-initialization-list: Public generic functions
result-initialization-list: Public generic functions
result-initialization-list: Public generic functions
row-index: Private ordinary functions
run-algorithm: Public generic functions
run-algorithm: Public generic functions
run-algorithm: Public generic functions
run-algorithm: Public generic functions

S
same-events: Private ordinary functions
scan-for-clusters-of-invalid-size: Private ordinary functions
seed: Public ordinary functions
select-initial-medoids: Private ordinary functions
select-medoids-attempts-count: Private generic functions
select-medoids-attempts-count: Private generic functions
select-new-medoids: Private ordinary functions
select-random-cluster-subsets: Private ordinary functions
silhouette: Public generic functions
silhouette: Public generic functions
silhouette: Public generic functions
silhouette-sample-count: Public generic functions
silhouette-sample-count: Public generic functions
silhouette-sample-count: Public generic functions
silhouette-sample-size: Public generic functions
silhouette-sample-size: Public generic functions
silhouette-sample-size: Public generic functions
sinkhorn: Public ordinary functions
sinkhorn-optimal-transport-matrix: Private ordinary functions
split-merge-attempts-count: Private generic functions
split-merge-attempts-count: Private generic functions
split-threshold: Private generic functions
split-threshold: Private generic functions
square-row/column->half-matrix-index: Public ordinary functions
sum-row: Private ordinary functions
svr: Public ordinary functions
swap-if: Public ordinary functions

T
to-cluster-contents: Private ordinary functions
transform: Public ordinary functions

U
unfinished-clusters-p: Private ordinary functions
update-grid: Private ordinary functions

W
with-grid-mapping-resources: Private macros

Y
y: Private generic functions
y: Private generic functions

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A.3 Variables

Jump to:   %   +  
C   S  
Index Entry  Section

%
%cluster-contents: Private classes
%cluster-indexes: Public classes
%cluster-size: Private classes
%clusters: Private classes
%d: Private classes
%data: Public classes
%data: Public classes
%distance-function: Public classes
%distance-matrix: Private classes
%distance-matrix: Private classes
%distortion: Private classes
%distortion-epsilon: Public classes
%indexes: Public classes
%indexes: Public classes
%iterations: Public classes
%key-function: Public classes
%max-neighbor: Public classes
%medoids: Private classes
%medoids: Private classes
%medoids-count: Public classes
%medoids-count: Public classes
%medoids-count: Public classes
%medoids-count: Private classes
%merge-threshold: Public classes
%parallelp: Public classes
%parameters: Private classes
%select-medoids-attempts-count: Public classes
%silhouette: Public classes
%silhouette-sample-count: Public classes
%silhouette-sample-size: Public classes
%split-merge-attempts-count: Public classes
%split-threshold: Public classes
%unfinished-clusters: Private classes
%y: Private classes

+
+sqrt2+: Private constants

C
Constant, +sqrt2+: Private constants

S
Slot, %cluster-contents: Private classes
Slot, %cluster-indexes: Public classes
Slot, %cluster-size: Private classes
Slot, %clusters: Private classes
Slot, %d: Private classes
Slot, %data: Public classes
Slot, %data: Public classes
Slot, %distance-function: Public classes
Slot, %distance-matrix: Private classes
Slot, %distance-matrix: Private classes
Slot, %distortion: Private classes
Slot, %distortion-epsilon: Public classes
Slot, %indexes: Public classes
Slot, %indexes: Public classes
Slot, %iterations: Public classes
Slot, %key-function: Public classes
Slot, %max-neighbor: Public classes
Slot, %medoids: Private classes
Slot, %medoids: Private classes
Slot, %medoids-count: Public classes
Slot, %medoids-count: Public classes
Slot, %medoids-count: Public classes
Slot, %medoids-count: Private classes
Slot, %merge-threshold: Public classes
Slot, %parallelp: Public classes
Slot, %parameters: Private classes
Slot, %select-medoids-attempts-count: Public classes
Slot, %silhouette: Public classes
Slot, %silhouette-sample-count: Public classes
Slot, %silhouette-sample-size: Public classes
Slot, %split-merge-attempts-count: Public classes
Slot, %split-threshold: Public classes
Slot, %unfinished-clusters: Private classes
Slot, %y: Private classes

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A.4 Data types

Jump to:   A   B   C   D   E   F   G   H   I   K   L   M   P   R   S   T   U  
Index Entry  Section

A
algorithm-state: Public classes
algorithm-state: Private classes
algorithm-state: Private classes
algorithm-state: Private classes
aux-package.lisp: The clusters/aux-package․lisp file
average.lisp: The clusters/metric/average․lisp file

B
bhattacharyya.lisp: The clusters/distance/bhattacharyya․lisp file

C
clarans: The clusters/clarans module
Class, algorithm-state: Public classes
Class, algorithm-state: Private classes
Class, algorithm-state: Private classes
Class, algorithm-state: Private classes
Class, pam-result: Private classes
Class, parameters: Public classes
Class, parameters: Public classes
Class, parameters: Public classes
Class, parameters: Public classes
Class, parameters-holder: Private classes
Class, result: Public classes
clusters: The clusters system
clusters: The clusters package
clusters.asd: The clusters/clusters․asd file
clusters.aux-package: The clusters․aux-package package
clusters.clarans: The clusters․clarans package
clusters.distance: The clusters․distance package
clusters.fancy: The clusters․fancy package
clusters.k-means: The clusters․k-means package
clusters.metric: The clusters․metric package
clusters.pam: The clusters․pam package
clusters.utils: The clusters․utils package
common: The clusters/common module

D
distance: The clusters/distance module
docstrings.lisp: The clusters/metric/docstrings․lisp file
docstrings.lisp: The clusters/distance/docstrings․lisp file

E
earth-mover.lisp: The clusters/metric/earth-mover․lisp file
euclid.lisp: The clusters/metric/euclid․lisp file

F
File, aux-package.lisp: The clusters/aux-package․lisp file
File, average.lisp: The clusters/metric/average․lisp file
File, bhattacharyya.lisp: The clusters/distance/bhattacharyya․lisp file
File, clusters.asd: The clusters/clusters․asd file
File, docstrings.lisp: The clusters/metric/docstrings․lisp file
File, docstrings.lisp: The clusters/distance/docstrings․lisp file
File, earth-mover.lisp: The clusters/metric/earth-mover․lisp file
File, euclid.lisp: The clusters/metric/euclid․lisp file
File, functions.lisp: The clusters/common/functions․lisp file
File, generics.lisp: The clusters/common/generics․lisp file
File, generics.lisp: The clusters/pam/generics․lisp file
File, generics.lisp: The clusters/clarans/generics․lisp file
File, group-average.lisp: The clusters/metric/group-average․lisp file
File, hausdorff.lisp: The clusters/metric/hausdorff․lisp file
File, hellinger.lisp: The clusters/metric/hellinger․lisp file
File, lcs.lisp: The clusters/metric/lcs․lisp file
File, levenshtein.lisp: The clusters/metric/levenshtein․lisp file
File, maps.lisp: The clusters/utils/maps․lisp file
File, matrix.lisp: The clusters/utils/matrix․lisp file
File, methods.lisp: The clusters/common/methods․lisp file
File, methods.lisp: The clusters/pam/methods․lisp file
File, methods.lisp: The clusters/clarans/methods․lisp file
File, methods.lisp: The clusters/k-means/methods․lisp file
File, package.lisp: The clusters/utils/package․lisp file
File, package.lisp: The clusters/metric/package․lisp file
File, package.lisp: The clusters/distance/package․lisp file
File, package.lisp: The clusters/common/package․lisp file
File, package.lisp: The clusters/pam/package․lisp file
File, package.lisp: The clusters/clarans/package․lisp file
File, package.lisp: The clusters/k-means/package․lisp file
File, partition.lisp: The clusters/utils/partition․lisp file
File, random.lisp: The clusters/utils/random․lisp file
File, silhouette.lisp: The clusters/common/silhouette․lisp file
File, sinkhorn.lisp: The clusters/distance/sinkhorn․lisp file
File, svr.lisp: The clusters/metric/svr․lisp file
File, types.lisp: The clusters/common/types․lisp file
File, types.lisp: The clusters/pam/types․lisp file
File, types.lisp: The clusters/clarans/types․lisp file
File, types.lisp: The clusters/k-means/types․lisp file
File, utils.lisp: The clusters/utils/utils․lisp file
File, utils.lisp: The clusters/common/utils․lisp file
File, utils.lisp: The clusters/pam/utils․lisp file
File, utils.lisp: The clusters/clarans/utils․lisp file
File, utils.lisp: The clusters/k-means/utils․lisp file
functions.lisp: The clusters/common/functions․lisp file

G
generics.lisp: The clusters/common/generics․lisp file
generics.lisp: The clusters/pam/generics․lisp file
generics.lisp: The clusters/clarans/generics․lisp file
group-average.lisp: The clusters/metric/group-average․lisp file

H
hausdorff.lisp: The clusters/metric/hausdorff․lisp file
hellinger.lisp: The clusters/metric/hellinger․lisp file

I
index-array: Private types

K
k-means: The clusters/k-means module

L
lcs.lisp: The clusters/metric/lcs․lisp file
levenshtein.lisp: The clusters/metric/levenshtein․lisp file

M
maps.lisp: The clusters/utils/maps․lisp file
matrix.lisp: The clusters/utils/matrix․lisp file
methods.lisp: The clusters/common/methods․lisp file
methods.lisp: The clusters/pam/methods․lisp file
methods.lisp: The clusters/clarans/methods․lisp file
methods.lisp: The clusters/k-means/methods․lisp file
metric: The clusters/metric module
Module, clarans: The clusters/clarans module
Module, common: The clusters/common module
Module, distance: The clusters/distance module
Module, k-means: The clusters/k-means module
Module, metric: The clusters/metric module
Module, pam: The clusters/pam module
Module, utils: The clusters/utils module

P
Package, clusters: The clusters package
Package, clusters.aux-package: The clusters․aux-package package
Package, clusters.clarans: The clusters․clarans package
Package, clusters.distance: The clusters․distance package
Package, clusters.fancy: The clusters․fancy package
Package, clusters.k-means: The clusters․k-means package
Package, clusters.metric: The clusters․metric package
Package, clusters.pam: The clusters․pam package
Package, clusters.utils: The clusters․utils package
package.lisp: The clusters/utils/package․lisp file
package.lisp: The clusters/metric/package․lisp file
package.lisp: The clusters/distance/package․lisp file
package.lisp: The clusters/common/package․lisp file
package.lisp: The clusters/pam/package․lisp file
package.lisp: The clusters/clarans/package․lisp file
package.lisp: The clusters/k-means/package․lisp file
pam: The clusters/pam module
pam-result: Private classes
parameters: Public classes
parameters: Public classes
parameters: Public classes
parameters: Public classes
parameters-holder: Private classes
partition.lisp: The clusters/utils/partition․lisp file

R
random.lisp: The clusters/utils/random․lisp file
result: Public classes

S
silhouette.lisp: The clusters/common/silhouette․lisp file
sinkhorn.lisp: The clusters/distance/sinkhorn․lisp file
svr.lisp: The clusters/metric/svr․lisp file
System, clusters: The clusters system

T
Type, index-array: Private types
types.lisp: The clusters/common/types․lisp file
types.lisp: The clusters/pam/types․lisp file
types.lisp: The clusters/clarans/types․lisp file
types.lisp: The clusters/k-means/types․lisp file

U
utils: The clusters/utils module
utils.lisp: The clusters/utils/utils․lisp file
utils.lisp: The clusters/common/utils․lisp file
utils.lisp: The clusters/pam/utils․lisp file
utils.lisp: The clusters/clarans/utils․lisp file
utils.lisp: The clusters/k-means/utils․lisp file

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