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
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virtual
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( )
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Public member functions
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virtual double
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(
Classify the given feature vector. |
Friends
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friend struct
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Function details
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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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