CLPM Class Reference

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Detailed Description

Definition at line 44 of file LPM.h.

Inheritance diagram for CLPM:

List of all members.

Public Member Functions
	CLPM ()
virtual	~CLPM ()
virtual bool	train (CFeatures *data=NULL)
virtual EClassifierType	get_classifier_type ()
virtual void	set_features (CDotFeatures *feat)
void	set_C (float64_t c_neg, float64_t c_pos)
float64_t	get_C1 ()
float64_t	get_C2 ()
void	set_bias_enabled (bool enable_bias)
bool	get_bias_enabled ()
void	set_epsilon (float64_t eps)
float64_t	get_epsilon ()
virtual const char *	get_name () const
Protected Attributes
float64_t	C1
float64_t	C2
bool	use_bias
float64_t	epsilon

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Constructor & Destructor Documentation

CLPM

(

)

Definition at line 22 of file LPM.cpp.

~CLPM

(

)

[virtual]

Definition at line 28 of file LPM.cpp.

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Member Function Documentation

bool get_bias_enabled

(

)

Definition at line 90 of file LPM.h.

float64_t get_C1

(

)

Definition at line 86 of file LPM.h.

float64_t get_C2

(

)

Definition at line 87 of file LPM.h.

virtual EClassifierType get_classifier_type

(

)

[virtual]

get classifier type

Returns:

classifier type NONE

Reimplemented from CClassifier.

Definition at line 60 of file LPM.h.

float64_t get_epsilon

(

)

Definition at line 93 of file LPM.h.

virtual const char* get_name

(

void

)

const [virtual]

Returns:

object name

Reimplemented from CLinearClassifier.

Definition at line 96 of file LPM.h.

void set_bias_enabled

(

bool

enable_bias

)

Definition at line 89 of file LPM.h.

void set_C	(	float64_t	c_neg,
		float64_t	c_pos
	)

set C

Parameters:

	c_neg	new C constant for negatively labeled examples
	c_pos	new C constant for positively labeled examples

Definition at line 84 of file LPM.h.

void set_epsilon

(

float64_t

eps

)

Definition at line 92 of file LPM.h.

virtual void set_features

(

CDotFeatures *

feat

)

[virtual]

set features

Parameters:

feat

features to set

Reimplemented from CLinearClassifier.

Definition at line 69 of file LPM.h.

bool train

(

CFeatures *

data = NULL

)

[virtual]

train classifier

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 CClassifier.

Definition at line 32 of file LPM.cpp.

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Member Data Documentation

float64_t C1 [protected]

Definition at line 99 of file LPM.h.

float64_t C2 [protected]

Definition at line 100 of file LPM.h.

float64_t epsilon [protected]

Definition at line 102 of file LPM.h.

bool use_bias [protected]

Definition at line 101 of file LPM.h.

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

• LPM.h
• LPM.cpp