learn_sampset_boxlearn_sampset_boxLearnSampsetBoxLearnSampsetBox (Operator)

Name

learn_sampset_boxlearn_sampset_boxLearnSampsetBoxLearnSampsetBox — Train the classifier with one data set.

Warning

learn_sampset_boxlearn_sampset_boxLearnSampsetBoxLearnSampsetBoxLearnSampsetBox is obsolete and is only provided for reasons of backward compatibility.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.

Signature

Description

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

• Multithreading type: reentrant (runs in parallel with non-exclusive operators).
• Multithreading scope: global (may be called from any thread).
• Processed without parallelization.

This operator modifies the state of the following input parameter:

• ClassifHandleClassifHandleClassifHandleClassifHandleclassifHandle

Parameters

Result

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

create_class_boxcreate_class_boxCreateClassBoxCreateClassBoxCreateClassBox

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

Module

Foundation