Detailed Description

Class LinearClassifier is a generic interface for all kinds of linear classifiers.

A linear classifier computes

$f({\bf x})= {\bf w} \cdot {\bf x} + b$

where ${\bf w}$ are the weights assigned to each feature in training and $b$ the bias.

To implement a linear classifier all that is required is to define the train() function that delivers ${\bf w}$ above.

Note that this framework works with linear classifiers of arbitraty feature type, e.g. dense and sparse and even string based features. This is implemented by using CDotFeatures that may provide a mapping function $\Phi({\bf x})\mapsto {\cal R^D}$ encapsulating all the required operations (like the dot product). The decision function is thus

$f({\bf x})= {\bf w} \cdot \Phi({\bf x}) + b.$

The following linear classifiers are implemented

Linear Descriminant Analysis (CLDA)
Linear Programming Machines (CLPM, CLPBoost)
Perceptron (CPerceptron)
Linear SVMs (CSVMSGD, CLibLinear, CSVMOcas, CSVMLin, CSubgradientSVM)

See also:: CDotFeatures

Definition at line 60 of file LinearClassifier.h.

Inheritance diagram for CLinearClassifier:

[legend]

List of all members.

Public Member Functions
	CLinearClassifier ()
virtual	~CLinearClassifier ()
virtual float64_t	classify_example (int32_t vec_idx)
	get output for example "vec_idx"
void	get_w (float64_t *&dst_w, int32_t &dst_dims)
void	get_w (float64_t *dst_w, int32_t dst_dims)
void	set_w (float64_t *src_w, int32_t src_w_dim)
void	set_bias (float64_t b)
float64_t	get_bias ()
virtual bool	load (FILE *srcfile)
virtual bool	save (FILE *dstfile)
virtual void	set_features (CDotFeatures *feat)
virtual CLabels *	classify ()
virtual CLabels *	classify (CFeatures *data)
virtual CDotFeatures *	get_features ()
virtual const char *	get_name (void) const
Protected Attributes
int32_t	w_dim
float64_t *	w
float64_t	bias
CDotFeatures *	features

Constructor & Destructor Documentation

CLinearClassifier ( )

default constructor

Definition at line 16 of file LinearClassifier.cpp.

~CLinearClassifier ( ) [virtual]

Definition at line 26 of file LinearClassifier.cpp.

Member Function Documentation

CLabels * classify ( ) [virtual]

classify all examples

Returns:: resulting labels

Implements CClassifier.

Definition at line 46 of file LinearClassifier.cpp.

CLabels * classify ( CFeatures * data ) [virtual]

classify objects

Parameters:

data

(test)data to be classified

Returns:: classified labels

Implements CClassifier.

Definition at line 68 of file LinearClassifier.cpp.

virtual float64_t classify_example ( int32_t vec_idx ) [virtual]

get output for example "vec_idx"

Reimplemented from CClassifier.

Definition at line 68 of file LinearClassifier.h.

float64_t get_bias ( )

get bias

Returns:: bias

Definition at line 126 of file LinearClassifier.h.

virtual CDotFeatures* get_features ( ) [virtual]

get features

Returns:: features

Definition at line 173 of file LinearClassifier.h.

virtual const char* get_name ( void ) const [virtual]

Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.

Returns:: name of the SGSerializable

Implements CSGObject.

Reimplemented in CLDA, CLPBoost, CLPM, CPerceptron, CSubGradientLPM, CDomainAdaptationSVMLinear, CLibLinear, CSubGradientSVM, CSVMLin, CSVMOcas, and CSVMSGD.

Definition at line 180 of file LinearClassifier.h.

void get_w	(	float64_t **	dst_w,
		int32_t *	dst_dims
	)

get w (swig compatible)

Parameters:

	dst_w	store w in this argument
	dst_dims	dimension of w

Definition at line 90 of file LinearClassifier.h.

void get_w	(	float64_t *&	dst_w,
		int32_t &	dst_dims
	)

get w

Parameters:

	dst_w	store w in this argument
	dst_dims	dimension of w

Definition at line 78 of file LinearClassifier.h.

bool load ( FILE * srcfile ) [virtual]

load from file

Parameters:

srcfile

file to load from

Returns:: if loading was successful

Reimplemented from CClassifier.

Definition at line 32 of file LinearClassifier.cpp.

bool save ( FILE * dstfile ) [virtual]

save to file

Parameters:

dstfile

file to save to

Returns:: if saving was successful

Reimplemented from CClassifier.

Definition at line 39 of file LinearClassifier.cpp.

void set_bias ( float64_t b )

set bias

Parameters:

b

new bias

Definition at line 117 of file LinearClassifier.h.

virtual void set_features ( CDotFeatures * feat ) [virtual]

set features

Parameters:

feat

features to set

Reimplemented in CLDA, CLPBoost, and CLPM.

Definition at line 149 of file LinearClassifier.h.

void set_w	(	float64_t *	src_w,
		int32_t	src_w_dim
	)

set w

Parameters:

	src_w	new w
	src_w_dim	dimension of new w

Definition at line 105 of file LinearClassifier.h.

Member Data Documentation

float64_t bias [protected]

bias

Definition at line 189 of file LinearClassifier.h.

CDotFeatures* features [protected]

features

Definition at line 191 of file LinearClassifier.h.

float64_t* w [protected]

w

Definition at line 187 of file LinearClassifier.h.

int32_t w_dim [protected]

dimension of w

Definition at line 185 of file LinearClassifier.h.

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

CLinearClassifier Class Reference

Detailed Description

Public Member Functions

Protected Attributes

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation