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classPiiKnnClassifier

#include <PiiKnnClassifier.h>

K nearest neighbors classifier.

Inherits PiiVectorQuantizer< SampleSet >

Description

The k-NN classifier considers the k code vectors closest to an unknown sample. The winning class index is chosen by voting among the k closest neighbors.

Public types

typedef PiiSampleSet::Traits< SampleSet >::ConstFeatureIterator

Constructors and destructor

(
  • PiiDistanceMeasure< SampleSet > * measure
)

Creates a new k-NN classifier that uses measure to measure distances between samples.

Creates a new k-NN classifier with the default distance measure (PiiSquaredGeometricDistance).

Public member functions

virtual double
(
  • ConstFeatureIterator featureVector
)

Returns the class label of the closest model sample.

QVector< double > &

Returns a modifiable reference to the class labels.

QVector< double >

Returns the class labels.

virtual int
(
  • ConstFeatureIterator featureVector
  • double * distance
)

Returns the index of the closest model sample in the winning class selected by the k nearest neighbors rule.

int
( )

Returns the the current value for k.

void
( )

Sets the class labels.

void
(
  • int k
)

Sets the number of closest neighbors to find when classifying an unknown sample.

Function details

  • PiiKnnClassifier

    (
    • PiiDistanceMeasure< SampleSet > * measure
    )

    Creates a new k-NN classifier that uses measure to measure distances between samples.

    The value for k is initialized to 5.

  • PiiKnnClassifier

    ()

    Creates a new k-NN classifier with the default distance measure (PiiSquaredGeometricDistance).

    The value for k is initialized to 5.

  • ~PiiKnnClassifier

    ()
  • virtual double classify

    (
    • ConstFeatureIterator featureVector
    )
    [virtual]

    Returns the class label of the closest model sample.

    If the distance to the closest sample is too large (see PiiVectorQuantizer::setRejectTreshold()), or there is no class label for the closest sample, NaN will be returned.

    Reimplemented from PiiVectorQuantizer.

  • QVector< double > & classLabels

    ()

    Returns a modifiable reference to the class labels.

  • QVector< double > classLabels

    ()

    Returns the class labels.

  • virtual int findClosestMatch

    (
    • ConstFeatureIterator featureVector
    • double * distance
    )
    [virtual]

    Returns the index of the closest model sample in the winning class selected by the k nearest neighbors rule.

    Reimplemented from PiiVectorQuantizer.

  • int getK

    ()

    Returns the the current value for k.

  • void setClassLabels

    ( )

    Sets the class labels.

  • void setK

    (
    • int k
    )

    Sets the number of closest neighbors to find when classifying an unknown sample.

    If k is set to one, the classifier works as a nearest-neighbor classifier.

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