LearningAlgorithm Class Reference

Inheritance diagram for LearningAlgorithm:

[legend]Collaboration diagram for LearningAlgorithm:


Constructors
	LearningAlgorithm (BaseNeuralNet *net)
virtual	~LearningAlgorithm ()
Interface
BaseNeuralNet *	net ()
virtual void	learn ()=0
virtual void	learn (const Pattern &)=0
virtual void	learnOnSet (const PatternSet &set)
virtual Real	calculateMSE (const Pattern &)=0
virtual Real	calculateMSEOnSet (const PatternSet &set)
Real	calculateRMSD (const Pattern &p)
Real	calculateRMSDOnSet (const PatternSet &p)

Detailed Description

The LearningAlgorithm object is a the abstract class from which to implement learning algorithms

LearningAlgorithm ( BaseNeuralNet * net )

Constructor

virtual ~LearningAlgorithm ( ) [virtual]

Destructor

BaseNeuralNet* net ( ) [inline]

Return the BaseNeuralNet setted

virtual void learn ( ) [pure virtual]

a single step of learning algorithm

virtual void learn ( const Pattern & ) [pure virtual]

Modify the object tring to learn the pattern passed

virtual void learnOnSet ( const PatternSet & set ) [inline, virtual]

Modify the object tring to learn all patterns present into PatternSet passed

virtual Real calculateMSE ( const Pattern & ) [pure virtual]

Calculate the Mean Square Error respect to Pattern passed

virtual Real calculateMSEOnSet ( const PatternSet & set ) [inline, virtual]

Calculate the Mean Square Error respect to all Patterns passed

Real calculateRMSD ( const Pattern & p ) [inline]

Calculate the Root Mean Square Deviation, i.e. the square root of MSE

Real calculateRMSDOnSet ( const PatternSet & p ) [inline]

Calculate the Root Mean Square Deviation, i.e. the square root of MSE

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

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