learn_sampset_boxT_learn_sampset_boxLearnSampsetBoxLearnSampsetBox (Operator)


learn_sampset_boxT_learn_sampset_boxLearnSampsetBoxLearnSampsetBox — Train the classifier with one data set.


learn_sampset_boxlearn_sampset_boxLearnSampsetBoxLearnSampsetBoxLearnSampsetBox is obsolete and is only provided for reasons of backward compatibility. New applications should use the MLP, SVM, KNN or GMM operators instead.


learn_sampset_box( : : ClassifHandle, SampKey, Outfile, NSamples, StopError, ErrorN : )

Herror T_learn_sampset_box(const Htuple ClassifHandle, const Htuple SampKey, const Htuple Outfile, const Htuple NSamples, const Htuple StopError, const Htuple ErrorN)

void LearnSampsetBox(const HTuple& ClassifHandle, const HTuple& SampKey, const HTuple& Outfile, const HTuple& NSamples, const HTuple& StopError, const HTuple& ErrorN)

void HFeatureSet::LearnSampsetBox(const HClassBox& ClassifHandle, const HString& Outfile, Hlong NSamples, double StopError, Hlong ErrorN) const

void HFeatureSet::LearnSampsetBox(const HClassBox& ClassifHandle, const char* Outfile, Hlong NSamples, double StopError, Hlong ErrorN) const

void HFeatureSet::LearnSampsetBox(const HClassBox& ClassifHandle, const wchar_t* Outfile, Hlong NSamples, double StopError, Hlong ErrorN) const   (Windows only)

void HClassBox::LearnSampsetBox(const HFeatureSet& SampKey, const HString& Outfile, Hlong NSamples, double StopError, Hlong ErrorN) const

void HClassBox::LearnSampsetBox(const HFeatureSet& SampKey, const char* Outfile, Hlong NSamples, double StopError, Hlong ErrorN) const

void HClassBox::LearnSampsetBox(const HFeatureSet& SampKey, const wchar_t* Outfile, Hlong NSamples, double StopError, Hlong ErrorN) const   (Windows only)

static void HOperatorSet.LearnSampsetBox(HTuple classifHandle, HTuple sampKey, HTuple outfile, HTuple NSamples, HTuple stopError, HTuple errorN)

void HFeatureSet.LearnSampsetBox(HClassBox classifHandle, string outfile, int NSamples, double stopError, int errorN)

void HClassBox.LearnSampsetBox(HFeatureSet sampKey, string outfile, int NSamples, double stopError, int errorN)


learn_sampset_boxlearn_sampset_boxLearnSampsetBoxLearnSampsetBoxLearnSampsetBox trains the classifier with data for the key SampKeySampKeySampKeySampKeysampKey (see read_sampsetread_sampsetReadSampsetReadSampsetReadSampset). The training sequence is terminated at least after NSamplesNSamplesNSamplesNSamplesNSamples examples. If NSamplesNSamplesNSamplesNSamplesNSamples is bigger than the number of examples in SampKeySampKeySampKeySampKeysampKey, then a cyclic start at the beginning occurs. If the error underpasses the value StopErrorStopErrorStopErrorStopErrorstopError, then the training sequence is prematurely terminated. StopErrorStopErrorStopErrorStopErrorstopError is calculated with N / ErrorN. Whereby N means the number of examples which were wrong classified during the last ErrorNErrorNErrorNErrorNerrorN training examples. Typically ErrorNErrorNErrorNErrorNerrorN is the number of examples in SampKeySampKeySampKeySampKeysampKey and NSamplesNSamplesNSamplesNSamplesNSamples is a multiple of it. If you want a data set with 100 examples to run 5 times at most and if you want it to terminate with an error lower than 5%, then the corresponding values are NSamplesNSamplesNSamplesNSamplesNSamples = 500, ErrorNErrorNErrorNErrorNerrorN = 100 and StopErrorStopErrorStopErrorStopErrorstopError = 0.05. A protocol of the training activity is going to be written in file OutfileOutfileOutfileOutfileoutfile.

Execution Information

This operator modifies the state of the following input parameter:

During execution of this operator, access to the value of this parameter must be synchronized if it is used across multiple threads.


ClassifHandleClassifHandleClassifHandleClassifHandleclassifHandle (input_control, state is modified)  class_box HClassBox, HTupleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of the classifier.

SampKeySampKeySampKeySampKeysampKey (input_control)  feature_set HFeatureSet, HTupleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Number of the data set to train.

OutfileOutfileOutfileOutfileoutfile (input_control)  filename.write HTupleHTupleHtuple (string) (string) (HString) (char*)

Name of the protocol file.

Default value: 'training_prot' "training_prot" "training_prot" "training_prot" "training_prot"

NSamplesNSamplesNSamplesNSamplesNSamples (input_control)  integer HTupleHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Number of arrays of attributes to learn.

Default value: 500

StopErrorStopErrorStopErrorStopErrorstopError (input_control)  real HTupleHTupleHtuple (real) (double) (double) (double)

Classification error for termination.

Default value: 0.05

ErrorNErrorNErrorNErrorNerrorN (input_control)  integer HTupleHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Error during the assignment.

Default value: 100


learn_sampset_boxlearn_sampset_boxLearnSampsetBoxLearnSampsetBoxLearnSampsetBox returns 2 (H_MSG_TRUE). An exception is raised if key SampKeySampKeySampKeySampKeysampKey does not exist or there are problems while opening the file.

Possible Predecessors


Possible Successors

test_sampset_boxtest_sampset_boxTestSampsetBoxTestSampsetBoxTestSampsetBox, enquire_class_boxenquire_class_boxEnquireClassBoxEnquireClassBoxEnquireClassBox, write_class_boxwrite_class_boxWriteClassBoxWriteClassBoxWriteClassBox, close_class_boxclose_class_boxCloseClassBoxCloseClassBoxCloseClassBox, clear_sampsetclear_sampsetClearSampsetClearSampsetClearSampset

See also

test_sampset_boxtest_sampset_boxTestSampsetBoxTestSampsetBoxTestSampsetBox, enquire_class_boxenquire_class_boxEnquireClassBoxEnquireClassBoxEnquireClassBox, learn_class_boxlearn_class_boxLearnClassBoxLearnClassBoxLearnClassBox, read_sampsetread_sampsetReadSampsetReadSampsetReadSampset