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classPiiClassifier

#include <PiiClassifier.h>

An interface for classification and regression algorithms.

Inherited by PiiBoostClassifier< SampleSet >, PiiDecisionStump< SampleSet >, PiiKernelAdatron< SampleSet >, PiiKernelPerceptron< SampleSet >, PiiPerceptron< SampleSet >, PiiVectorQuantizer< SampleSet >

Description

A classifier is an algorithm that maps an N-dimensional feature vector X into to a set of discrete class labels . In regression, the algorithm maps X to a continuous value .

Constructors and destructor

virtual

Public member functions

virtual double
(
  • typename PiiSampleSet::Traits< SampleSet >::ConstFeatureIterator featureVector
)  = 0

Classify the given feature vector.

Friends

friend struct

Function details

  • virtual ~PiiClassifier

    ()
    [inline, virtual]
  • template<class Archive>

    void serialize

    (
    • Archive &
    • const unsigned int
    )
    [inline]
  • virtual double classify

    (
    • typename PiiSampleSet::Traits< SampleSet >::ConstFeatureIterator featureVector
    )
    [pure virtual]

    Classify the given feature vector.

    The algorithm may vary from a simple nearest neighbor rule to support vector regression. The only requirement is that the classifier yields a class index or a continuous regression as a result. Errors are indicated by returning a NaN.

    Parameters
    featureVector

    the feature vector of the sample to be classified

    Returns

    a zero-based class index in classification, or a value in [0,1] in regression. NaN means that the sample could not be classified.

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