55 #ifndef BASICCVADAPTER_HH 56 #define BASICCVADAPTER_HH 74 typename PROBLEM = GroupedTrainingData<FV>,
75 typename STDATA = StDataASCII>
246 virtual int doFullCV(
const std::vector<int>& subsetIndexByUID,
247 std::vector<double>& predictedClassLabelByUID) = 0;
272 int detailLevel = 1) = 0;
275 int detailLevel = 1) = 0;
virtual double classificationDelta() const =0
virtual void setProgressReporter(ProgressReporter *pr)=0
set progress reporter object.
virtual void updateKernelCache()=0
call updateKernelCache() of selected svm with given problem.
virtual void saveParameters(STDATA &stData)=0
store all parameters of the SVM to given mapstructured data
virtual void setStoreClassificationDetailsFlag(bool f)=0
virtual const std::vector< StDataASCII > & classificationDetailsByUID() const =0
get classification details for each uid from last full CV or parital CV.
virtual const PROBLEM * trainingData() const =0
get pointer to training data, that was set with setTrainingData().
virtual void loadParameters(STDATA &stData)=0
Read all parameters (e.g.
virtual bool getStoreClassificationDetailsFlag() const =0
virtual void clearKernelCache()=0
call clearKernelCache() of selected svm.
virtual ~BasicCVAdapter()
virtual void setTrainingData(const PROBLEM *problem)=0
set the training data.
virtual void saveStatistics(STDATA &statistics, int detailLevel=1)=0
save cross validation statistics.
virtual void preprocessTrainingData()=0
trains all two-class SVM's with the whole data set.
virtual int doFullCV(const std::vector< int > &subsetIndexByUID, std::vector< double > &predictedClassLabelByUID)=0
do a full cross validation.
virtual void saveOnlyKernelParameters(StDataASCII &stData)=0
save only Kernel Parameters (this is used for user information and to detect in grid search...
virtual void setClassificationDelta(double d)=0
The StDataASCII class is a container for "structured data", that is kept completly in memory...