ClassesClasses | | Operators

clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvm (Operator)

Name

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

Signature

clear_samples_class_svm( : : SVMHandle : )

Herror clear_samples_class_svm(const Hlong SVMHandle)

Herror T_clear_samples_class_svm(const Htuple SVMHandle)

void ClearSamplesClassSvm(const HTuple& SVMHandle)

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

void HClassSvm::ClearSamplesClassSvm() const

static void HOperatorSet.ClearSamplesClassSvm(HTuple SVMHandle)

static void HClassSvm.ClearSamplesClassSvm(HClassSvm[] SVMHandle)

void HClassSvm.ClearSamplesClassSvm()

Description

clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvm clears all training samples that have been added to the support vector machine (SVM) SVMHandleSVMHandleSVMHandleSVMHandleSVMHandle with add_sample_class_svmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvmAddSampleClassSvm or read_samples_class_svmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmReadSamplesClassSvm. clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvm should only be used if the SVM is trained in the same process that uses the SVM for classification with classify_class_svmclassify_class_svmClassifyClassSvmClassifyClassSvmClassifyClassSvm. In this case, the memory required for the training samples can be freed with clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvm, 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_svmwrite_class_svmWriteClassSvmWriteClassSvmWriteClassSvm, it is typically unnecessary to call clear_samples_class_svmclear_samples_class_svmClearSamplesClassSvmClearSamplesClassSvmClearSamplesClassSvm because write_class_svmwrite_class_svmWriteClassSvmWriteClassSvmWriteClassSvm does not save the training samples, and hence the online process, which reads the SVM with read_class_svmread_class_svmReadClassSvmReadClassSvmReadClassSvm, requires no memory for the training samples.

Execution Information

This operator modifies the state of the following input parameter:

The value of this parameter may not be shared across multiple threads without external synchronization.

Parameters

SVMHandleSVMHandleSVMHandleSVMHandleSVMHandle (input_control, state is modified)  class_svm(-array) HClassSvm, HTupleHTupleHtuple (integer) (IntPtr) (Hlong) (Hlong)

SVM handle.

Result

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

Possible Predecessors

train_class_svmtrain_class_svmTrainClassSvmTrainClassSvmTrainClassSvm, write_samples_class_svmwrite_samples_class_svmWriteSamplesClassSvmWriteSamplesClassSvmWriteSamplesClassSvm

See also

create_class_svmcreate_class_svmCreateClassSvmCreateClassSvmCreateClassSvm, clear_class_svmclear_class_svmClearClassSvmClearClassSvmClearClassSvm, add_sample_class_svmadd_sample_class_svmAddSampleClassSvmAddSampleClassSvmAddSampleClassSvm, read_samples_class_svmread_samples_class_svmReadSamplesClassSvmReadSamplesClassSvmReadSamplesClassSvm

Module

Foundation


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