CVwAdaptiveLearner Class Reference

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Detailed Description

VwAdaptiveLearner uses an adaptive subgradient technique to update weights.

It uses two elements in the weight vector per feature and maintains individual learning rates for each feature. For details, refer to the VW tutorial.

Definition at line 31 of file VwAdaptiveLearner.h.

Inheritance diagram for CVwAdaptiveLearner:

List of all members.

Public Member Functions
	CVwAdaptiveLearner ()
	CVwAdaptiveLearner (CVwRegressor *regressor, CVwEnvironment *vw_env)
virtual	~CVwAdaptiveLearner ()
virtual void	train (VwExample *&ex, float32_t update)
virtual const char *	get_name () const

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Constructor & Destructor Documentation

CVwAdaptiveLearner

(

)

Default constructor

Definition at line 20 of file VwAdaptiveLearner.cpp.

CVwAdaptiveLearner	(	CVwRegressor *	regressor,
		CVwEnvironment *	vw_env
	)

Constructor, initializes regressor and environment

Parameters:

	regressor	regressor to use
	vw_env	environment to use

Definition at line 25 of file VwAdaptiveLearner.cpp.

~CVwAdaptiveLearner

(

)

[virtual]

Destructor

Definition at line 30 of file VwAdaptiveLearner.cpp.

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Member Function Documentation

virtual const char* get_name

(

)

const [virtual]

Return the name of the object

Returns:

VwAdaptiveLearner

Reimplemented from CVwLearner.

Definition at line 65 of file VwAdaptiveLearner.h.

void train	(	VwExample *&	ex,
		float32_t	update
	)			[virtual]

Train on one example, given the update

Parameters:

	ex	example
	update	the update

Implements CVwLearner.

Definition at line 34 of file VwAdaptiveLearner.cpp.

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

• VwAdaptiveLearner.h
• VwAdaptiveLearner.cpp