Public Member Functions

CVwAdaptiveLearner Class Reference

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:
Inheritance graph

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

Constructor & Destructor Documentation

Default constructor

Definition at line 20 of file VwAdaptiveLearner.cpp.

CVwAdaptiveLearner ( 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 VwAdaptiveLearner.cpp.

~CVwAdaptiveLearner (  )  [virtual]


Definition at line 30 of file VwAdaptiveLearner.cpp.

Member Function Documentation

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

Return the name of the object


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

ex example
update the update

Implements CVwLearner.

Definition at line 34 of file VwAdaptiveLearner.cpp.

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SHOGUN Machine Learning Toolbox - Documentation