Public Member Functions

CVwNonAdaptiveLearner Class Reference

Detailed Description

VwNonAdaptiveLearner uses a standard gradient descent weight update rule.

The weight vector is updated by adding the corresponding feature multiplied by the update factor for the example.

Definition at line 30 of file VwNonAdaptiveLearner.h.

Inheritance diagram for CVwNonAdaptiveLearner:
Inheritance graph

List of all members.

Public Member Functions

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

Constructor & Destructor Documentation

Default constructor

Definition at line 20 of file VwNonAdaptiveLearner.cpp.

CVwNonAdaptiveLearner ( CVwRegressor regressor,
CVwEnvironment vw_env 

Constructor, initializes regressor and environment

regressor regressor to use
vw_env environment to use

Definition at line 25 of file VwNonAdaptiveLearner.cpp.

~CVwNonAdaptiveLearner (  )  [virtual]


Definition at line 30 of file VwNonAdaptiveLearner.cpp.

Member Function Documentation

virtual const char* get_name (  )  const [virtual]

Return the name of the object


Reimplemented from CVwLearner.

Definition at line 64 of file VwNonAdaptiveLearner.h.

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

Train on one example, given the update

ex example
update the update

Implements CVwLearner.

Definition at line 34 of file VwNonAdaptiveLearner.cpp.

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SHOGUN Machine Learning Toolbox - Documentation