COnlineLinearMachine Class Reference

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Detailed Description

Class OnlineLinearMachine is a generic interface for linear machines like classifiers which work through online algorithms.

A linear classifier computes

where are the weights assigned to each feature in training and the bias.

To implement a linear classifier all that is required is to define the train() function that delivers above.

Note that this framework works with linear classifiers of arbitrary feature type, e.g. dense and sparse and even string based features. This is implemented by using CStreamingDotFeatures that may provide a mapping function encapsulating all the required operations (like the dot product). The decision function is thus

Definition at line 49 of file OnlineLinearMachine.h.

Inheritance diagram for COnlineLinearMachine:

List of all members.

Public Member Functions
	COnlineLinearMachine ()
virtual	~COnlineLinearMachine ()
virtual void	get_w (float32_t *&dst_w, int32_t &dst_dims)
virtual void	get_w (float64_t *&dst_w, int32_t &dst_dims)
virtual SGVector< float32_t >	get_w ()
virtual void	set_w (float32_t *src_w, int32_t src_w_dim)
virtual void	set_w (float64_t *src_w, int32_t src_w_dim)
virtual void	set_bias (float32_t b)
virtual float32_t	get_bias ()
virtual bool	load (FILE *srcfile)
virtual bool	save (FILE *dstfile)
virtual void	set_features (CStreamingDotFeatures *feat)
virtual CLabels *	apply ()
virtual CLabels *	apply (CFeatures *data)
virtual float64_t	apply (int32_t vec_idx)
	get output for example "vec_idx"
virtual float32_t	apply (float32_t *vec, int32_t len)
virtual float32_t	apply_to_current_example ()
virtual CStreamingDotFeatures *	get_features ()
virtual const char *	get_name () const
Protected Attributes
int32_t	w_dim
float32_t *	w
float32_t	bias
CStreamingDotFeatures *	features

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Constructor & Destructor Documentation

COnlineLinearMachine

(

)

default constructor

Definition at line 16 of file OnlineLinearMachine.cpp.

~COnlineLinearMachine

(

)

[virtual]

Definition at line 24 of file OnlineLinearMachine.cpp.

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Member Function Documentation

CLabels * apply

(

)

[virtual]

apply linear machine to all examples

Returns:

resulting labels

Implements CMachine.

Definition at line 47 of file OnlineLinearMachine.cpp.

CLabels * apply

(

CFeatures *

data

)

[virtual]

apply linear machine to data

Parameters:

data

(test)data to be classified

Returns:

classified labels

Implements CMachine.

Definition at line 74 of file OnlineLinearMachine.cpp.

virtual float64_t apply

(

int32_t

vec_idx

)

[virtual]

get output for example "vec_idx"

Reimplemented from CMachine.

Definition at line 178 of file OnlineLinearMachine.h.

float32_t apply	(	float32_t *	vec,
		int32_t	len
	)			[virtual]

apply linear machine to one vector

Parameters:

	vec	feature vector
	len	length of vector

Returns:

classified label

Definition at line 84 of file OnlineLinearMachine.cpp.

float32_t apply_to_current_example

(

)

[virtual]

apply linear machine to vector currently being processed

Returns:

classified label

Definition at line 89 of file OnlineLinearMachine.cpp.

virtual float32_t get_bias

(

)

[virtual]

get bias

Returns:

bias

Definition at line 133 of file OnlineLinearMachine.h.

virtual CStreamingDotFeatures* get_features

(

)

[virtual]

get features

Returns:

features

Definition at line 205 of file OnlineLinearMachine.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 COnlineLibLinear, COnlineSVMSGD, and CVowpalWabbit.

Definition at line 212 of file OnlineLinearMachine.h.

virtual void get_w	(	float64_t *&	dst_w,
		int32_t &	dst_dims
	)			[virtual]

Get w as a _new_ float64_t array

Parameters:

	dst_w	store w in this argument
	dst_dims	dimension of w

Definition at line 74 of file OnlineLinearMachine.h.

virtual void get_w	(	float32_t *&	dst_w,
		int32_t &	dst_dims
	)			[virtual]

get w

Parameters:

	dst_w	store w in this argument
	dst_dims	dimension of w

Definition at line 61 of file OnlineLinearMachine.h.

virtual SGVector<float32_t> get_w

(

)

[virtual]

get w

Returns:

weight vector

Definition at line 87 of file OnlineLinearMachine.h.

bool load

(

FILE *

srcfile

)

[virtual]

load from file

Parameters:

srcfile

file to load from

Returns:

if loading was successful

Reimplemented from CMachine.

Definition at line 33 of file OnlineLinearMachine.cpp.

bool save

(

FILE *

dstfile

)

[virtual]

save to file

Parameters:

dstfile

file to save to

Returns:

if saving was successful

Reimplemented from CMachine.

Definition at line 40 of file OnlineLinearMachine.cpp.

virtual void set_bias

(

float32_t

b

)

[virtual]

set bias

Parameters:

b

new bias

Definition at line 124 of file OnlineLinearMachine.h.

virtual void set_features

(

CStreamingDotFeatures *

feat

)

[virtual]

set features

Parameters:

feat

features to set

Definition at line 156 of file OnlineLinearMachine.h.

virtual void set_w	(	float64_t *	src_w,
		int32_t	src_w_dim
	)			[virtual]

Set weight vector from a float64_t vector

Parameters:

	src_w	new w
	src_w_dim	dimension of new w

Definition at line 111 of file OnlineLinearMachine.h.

virtual void set_w	(	float32_t *	src_w,
		int32_t	src_w_dim
	)			[virtual]

set w

Parameters:

	src_w	new w
	src_w_dim	dimension of new w

Definition at line 97 of file OnlineLinearMachine.h.

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Member Data Documentation

float32_t bias [protected]

bias

Definition at line 220 of file OnlineLinearMachine.h.

CStreamingDotFeatures* features [protected]

features

Reimplemented in CVowpalWabbit.

Definition at line 222 of file OnlineLinearMachine.h.

float32_t* w [protected]

w

Definition at line 218 of file OnlineLinearMachine.h.

int32_t w_dim [protected]

dimension of w

Definition at line 216 of file OnlineLinearMachine.h.

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

• OnlineLinearMachine.h
• OnlineLinearMachine.cpp