CHierarchical Class Reference

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Detailed Description

Agglomerative hierarchical single linkage clustering.

Starting with each object being assigned to its own cluster clusters are iteratively merged. Here the clusters are merged whose elements have minimum distance, i.e. the clusters A and B that obtain

are merged.

cf e.g. http://en.wikipedia.org/wiki/Data_clustering

Definition at line 37 of file Hierarchical.h.

Inheritance diagram for CHierarchical:

List of all members.

Public Member Functions
	CHierarchical ()
	CHierarchical (int32_t merges, CDistance *d)
virtual	~CHierarchical ()
virtual EClassifierType	get_classifier_type ()
virtual bool	load (FILE *srcfile)
virtual bool	save (FILE *dstfile)
void	set_merges (int32_t m)
int32_t	get_merges ()
SGVector< int32_t >	get_assignment ()
SGVector< float64_t >	get_merge_distances ()
SGMatrix< int32_t >	get_cluster_pairs ()
virtual const char *	get_name () const
Protected Member Functions
virtual bool	train_machine (CFeatures *data=NULL)
virtual void	store_model_features ()
virtual CLabels *	apply ()
virtual CLabels *	apply (CFeatures *data)
virtual float64_t	apply (int32_t num)
Protected Attributes
int32_t	merges
	the number of merges in hierarchical clustering
int32_t	dimensions
	number of dimensions
int32_t	assignment_size
	size of assignment table
int32_t *	assignment
	cluster assignment for the num_points
int32_t	table_size
	size of the below tables
int32_t *	pairs
	tuples of i/j
float64_t *	merge_distance
	distance at which pair i/j was added

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Constructor & Destructor Documentation

CHierarchical

(

)

default constructor

Definition at line 34 of file Hierarchical.cpp.

CHierarchical	(	int32_t	merges,
		CDistance *	d
	)

constructor

Parameters:

	merges	the merges
	d	distance

Definition at line 40 of file Hierarchical.cpp.

~CHierarchical

(

)

[virtual]

Definition at line 47 of file Hierarchical.cpp.

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Member Function Documentation

CLabels * apply

(

)

[protected, virtual]

NOT IMPLEMENTED

Reimplemented from CDistanceMachine.

Definition at line 204 of file Hierarchical.cpp.

CLabels * apply

(

CFeatures *

data

)

[protected, virtual]

NOT IMPLEMENTED

Reimplemented from CDistanceMachine.

Definition at line 199 of file Hierarchical.cpp.

float64_t apply

(

int32_t

num

)

[protected, virtual]

NOT IMPLEMENTED

Reimplemented from CDistanceMachine.

Definition at line 210 of file Hierarchical.cpp.

SGVector< int32_t > get_assignment

(

)

get assignment

Definition at line 178 of file Hierarchical.cpp.

EClassifierType get_classifier_type

(

)

[virtual]

get classifier type

Returns:

classifier type HIERARCHICAL

Reimplemented from CMachine.

Definition at line 54 of file Hierarchical.cpp.

SGMatrix< int32_t > get_cluster_pairs

(

)

get cluster pairs

Definition at line 188 of file Hierarchical.cpp.

SGVector< float64_t > get_merge_distances

(

)

get merge distance

Definition at line 183 of file Hierarchical.cpp.

int32_t get_merges

(

)

get merges

Returns:

merges

Definition at line 173 of file Hierarchical.cpp.

virtual const char* get_name

(

)

const [virtual]

Returns:

object name

Reimplemented from CDistanceMachine.

Definition at line 103 of file Hierarchical.h.

bool load

(

FILE *

srcfile

)

[virtual]

load distance machine from file

Parameters:

srcfile

file to load from

Returns:

if loading was successful

Reimplemented from CMachine.

Definition at line 158 of file Hierarchical.cpp.

bool save

(

FILE *

dstfile

)

[virtual]

save distance machine to file

Parameters:

dstfile

file to save to

Returns:

if saving was successful

Reimplemented from CMachine.

Definition at line 165 of file Hierarchical.cpp.

void set_merges

(

int32_t

m

)

set merges

Parameters:

m

new merges

Definition at line 75 of file Hierarchical.h.

void store_model_features

(

)

[protected, virtual]

TODO: Ensures cluster centers are in lhs of underlying distance Currently: does nothing.

Reimplemented from CDistanceMachine.

Definition at line 194 of file Hierarchical.cpp.

bool train_machine

(

CFeatures *

data = NULL

)

[protected, virtual]

estimate hierarchical clustering

Parameters:

data

training data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data)

Returns:

whether training was successful

Reimplemented from CMachine.

Definition at line 59 of file Hierarchical.cpp.

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Member Data Documentation

int32_t* assignment [protected]

cluster assignment for the num_points

Definition at line 141 of file Hierarchical.h.

int32_t assignment_size [protected]

size of assignment table

Definition at line 138 of file Hierarchical.h.

int32_t dimensions [protected]

number of dimensions

Definition at line 135 of file Hierarchical.h.

float64_t* merge_distance [protected]

distance at which pair i/j was added

Definition at line 150 of file Hierarchical.h.

int32_t merges [protected]

the number of merges in hierarchical clustering

Definition at line 132 of file Hierarchical.h.

int32_t* pairs [protected]

tuples of i/j

Definition at line 147 of file Hierarchical.h.

int32_t table_size [protected]

size of the below tables

Definition at line 144 of file Hierarchical.h.

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The documentation for this class was generated from the following files:

• Hierarchical.h
• Hierarchical.cpp