Classifier Class Reference

#include <Classifier.h>

Inheritance diagram for Classifier:

List of all members.

Public Member Functions
	Classifier (const string &name, const classifierparams &params)
virtual	~Classifier ()
virtual void	init (FeatureContainer *fc)
virtual membershiplist	getClusterMembership (const featurevector *sample)
virtual unsigned long	nextSample ()
virtual unsigned long	nextSample (const featurevector *sample)
virtual string	serialize () const
virtual void	unserialize (string data)
ClassifierAlgorithm *	getCa () const
virtual string	toString () const

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Detailed Description

Classifier Wrapper

The Classifier Class is a wrapper class that loads a dll containing the actual implementation during runtime.

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Constructor & Destructor Documentation

Classifier::Classifier (  const string &  name, const classifierparams &  params )

Creates the classifier Parameters: name  The name of the requested classifier implementation. params  A map of parameters to initialize the classifier.

Classifier::~Classifier (   )  [virtual]

Destructor

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Member Function Documentation

ClassifierAlgorithm* Classifier::getCa (   )  const [inline]

Return actual ClassifierAlgorithm instance

virtual membershiplist Classifier::getClusterMembership (  const featurevector *  sample  )  [inline, virtual]

Get membership vector This method returns the data for the next steps, which is a list of context classes found by the algorithm with associated membership values. These values specify the membership of the current feature values to each of the context classes in the interval [0; 1]. They can thus by seen as the probabilities that the context classes are currently active. Parameters: sample  The sample vector for which the membershiplist should be calculated Implements ClassifierAlgorithm.

virtual void Classifier::init (  FeatureContainer *  fc  )  [inline, virtual]

Initializer Initializes internal data structures of the classification/clustering algorithm. This usually involves constructing initial prototypes for cluster centers; thus, randomized feature vectors are necessary for the initialization. The getFeatureVector method of the passed FeatureContainer object may be called multiple times by the initialization. The given FeatureContainer is also used when nextSample() is called. Parameters: fc  The FeatureContainer from which the randomized feature vectors should be retrieved. See also: FeatureContainer::getFeatureVector nextSample() Implements ClassifierAlgorithm.

virtual unsigned long Classifier::nextSample (  const featurevector *  sample  )  [inline, virtual]

Fetch next sample vector Gets the next sample vector passed as parameter. Parameters: sample  samplevector Implements ClassifierAlgorithm.

virtual unsigned long Classifier::nextSample (   )  [inline, virtual]

Fetch next sample vector Gets the next sample vector from the configured feature source. This method calls nextSample and getSampleVector on the FeatureContainer given to the init method. See also: FeatureConteiner::nextSample FeatureContainer::getSampleVector Implements ClassifierAlgorithm.

virtual string Classifier::serialize (   )  const [inline, virtual]

Serialize a samples data to a string Returns: String representation of the samples data. Implements ClassifierAlgorithm.

virtual string Classifier::toString (   )  const [inline, virtual]

This is only for testing. Implements ClassifierAlgorithm.

virtual void Classifier::unserialize (  string  data  )  [inline, virtual]

Unserialize a samples data from a string Parameters: data  String representation of the samples data. Implements ClassifierAlgorithm.

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

• amw/src/cpp/cross/contextprediction/framework/Classifiers/Classifier.h
• amw/src/cpp/cross/contextprediction/framework/Classifiers/LinuxClassifier.cpp
• amw/src/cpp/cross/contextprediction/framework/Classifiers/WindowsClassifier.cpp

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