54 #ifndef BASICCVADAPTERTEMPL_HH 55 #define BASICCVADAPTERTEMPL_HH 75 _cv.setProgressReporter( pr);
80 _cv.loadParameters( stData);
85 _cv.loadParameters( stData);
90 _cv.loadParameters( stData);
95 _cv.saveParameters( stData);
100 _cv.saveParameters( stData);
105 _cv.svm()->twoClassSVM().kernel().saveParameters( stData);
110 _cv.setTrainingData( problem);
115 return _cv.trainingData();
120 _cv.updateKernelCache();
125 _cv.clearKernelCache();
131 _cv.preprocessTrainingData();
134 virtual int doFullCV(
const std::vector<int>& subsetIndexByUID,
135 std::vector<double>& predictedClassLabelByUID)
137 return _cv.doFullCV( subsetIndexByUID, predictedClassLabelByUID);
142 _cv.setClassificationDelta(d);
147 return _cv.classificationDelta();
152 _cv.setStoreClassificationDetailsFlag(f);
157 return _cv.getStoreClassificationDetailsFlag();
163 _cv.saveStatistics( statistics, detailLevel);
169 _cv.saveStatistics( statistics, detailLevel);
174 return _cv.classificationDetailsByUID();
virtual void loadParameters(StDataASCII &stData)
virtual void saveOnlyKernelParameters(StDataASCII &stData)
save only Kernel Parameters (this is used for user information and to detect in grid search...
virtual void saveParameters(StDataASCII &stData)
virtual void updateKernelCache()
call updateKernelCache() of selected svm with given problem.
The CrossValidator class provides a highly optimized cross validation algorithm.
virtual double classificationDelta() const
virtual void loadParameters(StDataCmdLine &stData)
Same as loadParameters, but for Parameters from command line.
virtual void saveParameters(STDATA &stData)
store all parameters of the SVM to given mapstructured data
virtual void saveStatistics(StDataASCII &statistics, int detailLevel=1)
virtual void saveStatistics(STDATA &statistics, int detailLevel=1)
save cross validation statistics.
virtual const PROBLEM * trainingData() const
get pointer to training data, that was set with setTrainingData().
virtual bool getStoreClassificationDetailsFlag() const
virtual void setClassificationDelta(double d)
virtual void loadParameters(STDATA &stData)
Read all parameters (e.g.
virtual const std::vector< StDataASCII > & classificationDetailsByUID() const
get classification details for each uid from last full CV or parital CV.
virtual int doFullCV(const std::vector< int > &subsetIndexByUID, std::vector< double > &predictedClassLabelByUID)
do a full cross validation.
virtual void preprocessTrainingData()
trains all two-class SVM's with the whole data set.
virtual void clearKernelCache()
call clearKernelCache() of selected svm.
virtual void setTrainingData(const PROBLEM *problem)
set the training data.
virtual void setStoreClassificationDetailsFlag(bool f)
The StDataASCII class is a container for "structured data", that is kept completly in memory...
virtual void setProgressReporter(ProgressReporter *pr)
set progress reporter object.