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clear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svmT_clear_samples_class_svm🔗

Short description🔗

clear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmclear_samples_class_svmT_clear_samples_class_svm — Clear the training data of a support vector machine.

Signature🔗

clear_samples_class_svm( class_svm SVMHandle )void ClearSamplesClassSvm( const HTuple& SVMHandle )static void HOperatorSet.ClearSamplesClassSvm( HTuple SVMHandle )def clear_samples_class_svm( svmhandle: MaybeSequence[HHandle] ) -> None

Herror T_clear_samples_class_svm( const Htuple SVMHandle )

static void HClassSvm::ClearSamplesClassSvm( const HClassSvmArray& SVMHandle )

void HClassSvm::ClearSamplesClassSvm( ) const

static void HClassSvm.ClearSamplesClassSvm( HClassSvm[] SVMHandle )

void HClassSvm.ClearSamplesClassSvm( )

Description🔗

clear_samples_class_svmClearSamplesClassSvm clears all training samples that have been added to the support vector machine (SVM) SVMHandleSVMHandlesvmhandle with add_sample_class_svmAddSampleClassSvm or read_samples_class_svmReadSamplesClassSvm. clear_samples_class_svmClearSamplesClassSvm should only be used if the SVM is trained in the same process that uses the SVM for classification with classify_class_svmClassifyClassSvm. In this case, the memory required for the training samples can be freed with clear_samples_class_svmClearSamplesClassSvm, and hence memory can be saved. In the normal usage, in which the SVM is trained offline and written to a file with write_class_svmWriteClassSvm, it is typically unnecessary to call clear_samples_class_svmClearSamplesClassSvm because write_class_svmWriteClassSvm does not save the training samples, and hence the online process, which reads the SVM with read_class_svmReadClassSvm, requires no memory for the training samples.

Execution information🔗

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:

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

Parameters🔗

SVMHandleSVMHandlesvmhandle (input_control, state is modified) class_svm(-array) → (handle)HTuple (HHandle)HClassSvm, HTuple (IntPtr)MaybeSequence[HHandle]Htuple (handle)

SVM handle.

Result🔗

If the parameters are valid the operator clear_samples_class_svmClearSamplesClassSvm returns the value 2 (H_MSG_TRUE). If necessary, an exception is raised.

Combinations with other operators🔗

Combinations

Possible predecessors

train_class_svmTrainClassSvm, write_samples_class_svmWriteSamplesClassSvm

See also

create_class_svmCreateClassSvm, clear_class_svmClearClassSvm, add_sample_class_svmAddSampleClassSvm, read_samples_class_svmReadSamplesClassSvm

Module🔗

Foundation