ClassificationDataSet< InClass, OutClass > Class Template Reference

#include <data_set.h>

Public Types
typedef InClass	In
	Class of input vectors. Usually a FeatureVector (vector of Feature) More...
typedef OutClass	Out
	Class of the target. Can be a double, string, unsigned, even a vector ... More...
typedef ClassificationTrainingSet< In, Out >	TS
	Training set. Set of vectors (training vectors), probably classified. More...

Public Member Functions
	ClassificationDataSet ()
virtual	~ClassificationDataSet ()
virtual Out	apply (const In &_in) const =0
virtual unsigned	output (const In &_in) const =0

Detailed Description

template<class InClass, class OutClass>
class ClassificationDataSet< InClass, OutClass >

Abstract Data Set class that should be used by all classification algorithms. This is the parent class for all algorithms that can be trained and applied in order to classify a set of data. A xmipp classification object must have: \1) A train method that accepts a set of feature vectors \2) An apply method that accepts an example and classifies it

Definition at line 44 of file data_set.h.

Member Typedef Documentation

In

template<class InClass, class OutClass>

typedef InClass ClassificationDataSet< InClass, OutClass >::In

Class of input vectors. Usually a FeatureVector (vector of Feature)

Definition at line 48 of file data_set.h.

Out

template<class InClass, class OutClass>

typedef OutClass ClassificationDataSet< InClass, OutClass >::Out

Class of the target. Can be a double, string, unsigned, even a vector ...

Definition at line 51 of file data_set.h.

TS

template<class InClass, class OutClass>

typedef ClassificationTrainingSet<In, Out> ClassificationDataSet< InClass, OutClass >::TS

Training set. Set of vectors (training vectors), probably classified.

Definition at line 54 of file data_set.h.

Constructor & Destructor Documentation

ClassificationDataSet()

template<class InClass, class OutClass>

ClassificationDataSet< InClass, OutClass >::ClassificationDataSet ( )

inline

Constructor. This constructor is empty.

Definition at line 60 of file data_set.h.

    {};

~ClassificationDataSet()

template<class InClass, class OutClass>

virtual ClassificationDataSet< InClass, OutClass >::~ClassificationDataSet ( )

inlinevirtual

Destructor. The default destructor

Definition at line 67 of file data_set.h.

    {};

Member Function Documentation

apply()

template<class InClass, class OutClass>

virtual Out ClassificationDataSet< InClass, OutClass >::apply ( const In &  _in ) const

pure virtual

Method to classify a feature vector It returns the 'class' to which the vector belongs Parameter: _in vcetor to test.

Returns

The result of classification.

Implemented in CodeBook.

output()

template<class InClass, class OutClass>

virtual unsigned ClassificationDataSet< InClass, OutClass >::output ( const In &  _in ) const

pure virtual

Method to classify an input vector. This method returns an unsigned integer that would correspond to the output neuron, the output codevector, or anything similar. If it makes no sense, it should be declared as private. Although it means many different things, it�s included here to have an uniform representation Parameter: _in input vector to test.

Returns

The result of classification.

Implemented in CodeBook.

---

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

• xmipp/libraries/classification/data_set.h