Machine Learning Library
CDatasetAlgorithm.h
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2  COPYRIGHT (C) 2003 APPLIED NEUROINFORMATIC GROUP - UNIVERSITY OF BIELEFELD.
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23 
24 
25 
26 #ifndef CDATASETALGORITHM_H
27 #define CDATASETALGORITHM_H
28 
29 #include "CDenseVector.h"
30 #include "CMatrix.h"
31 #include "CMetric.h"
32 #include "CDataset.h"
33 #include "CDatasetItem.h"
34 #include <vector>
35 #include <algorithm>
36 #include <ctime>
37 #include <iostream>
38 #include "CObject.h"
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40 
41 
42 
48 template <class Type>
50 
56 template <class Type>
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59 
66 template <class Type>
68 
76 template <class Type>
78 
88 template <class Type>
89 CDataset<Type> applyZScore(const CDataset<Type>& tDs, const CDenseVector<Type>& tMean, const CDenseVector<Type>& tVariance);
90 
100 template <class Type>
102 
103 
114 template <class Type>
116 
126 template <class Type>
127 CDataset<Type> applyScaleRange(const CDataset<Type>& tDs, const CDenseVector<Type>& tShift, const CDenseVector<Type>& tScale);
128 
129 
139 template <class Type>
141 
148 template <class Type>
149 CDataset<Type> normalize(const CDataset<Type>& rtDs, const CMetric<Type>& rtMetric);
150 
156 template <class Type>
157 CDataset<Type> removeProjection(const CDataset<Type>& rtDataset, const CDenseVector<Type>& rtVec);
158 
164 template <class Type>
165 void applyWeights(CDataset<Type>& rtDataset, const CDenseVector<Type>& rtWeights);
166 
170 template <class Type>
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173 
174 
175 
176 #endif
void normalizeInputDataEuclidean(CDataset< Type > &rtDs)
Base class for metrix objects.
Definition: CMetric.h:36
CDataset< Type > applyZScore(const CDataset< Type > &tDs, const CDenseVector< Type > &tMean, const CDenseVector< Type > &tVariance)
CDataset< Type > removeProjection(const CDataset< Type > &rtDataset, const CDenseVector< Type > &rtVec)
void applyWeights(CDataset< Type > &rtDataset, const CDenseVector< Type > &rtWeights)
CDataset< Type > zscore(const CDataset< Type > &tDs, CDenseVector< Type > &tMean, CDenseVector< Type > &tVariance)
CDenseVector< Type > maxElements(const CDataset< Type > &tDs)
Template object for vectors of single and double precision and integer.
Definition: CDenseVector.h:37
CDataset< Type > scaleRange(const CDataset< Type > &tDs, const CDenseVector< Type > tNewMin, const CDenseVector< Type > tNewMax, CDenseVector< Type > &tShift, CDenseVector< Type > &tScale)
CDataset< Type > applyScaleRange(const CDataset< Type > &tDs, const CDenseVector< Type > &tShift, const CDenseVector< Type > &tScale)
Manages pairs of input and output vectors.
Definition: CDataset.h:110
CDenseVector< Type > minElements(const CDataset< Type > &tDs)
CDataset< Type > centerInput(const CDataset< Type > &tDs, CDenseVector< Type > &tMean)
CDataset< Type > normalize(const CDataset< Type > &rtDs, const CMetric< Type > &rtMetric)