ClassesClasses | | Operators

clear_samples_class_mlpclear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlp (Operator)

Name

clear_samples_class_mlpclear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlp — Clear the training data of a multilayer perceptron.

Signature

clear_samples_class_mlp( : : MLPHandle : )

Herror clear_samples_class_mlp(const Hlong MLPHandle)

Herror T_clear_samples_class_mlp(const Htuple MLPHandle)

void ClearSamplesClassMlp(const HTuple& MLPHandle)

static void HClassMlp::ClearSamplesClassMlp(const HClassMlpArray& MLPHandle)

void HClassMlp::ClearSamplesClassMlp() const

static void HOperatorSet.ClearSamplesClassMlp(HTuple MLPHandle)

static void HClassMlp.ClearSamplesClassMlp(HClassMlp[] MLPHandle)

void HClassMlp.ClearSamplesClassMlp()

Description

clear_samples_class_mlpclear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlpClearSamplesClassMlp clears all training samples that have been added to the multilayer perceptron (MLP) MLPHandleMLPHandleMLPHandleMLPHandleMLPHandle with add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlpAddSampleClassMlp or read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpReadSamplesClassMlp. clear_samples_class_mlpclear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlpClearSamplesClassMlp should only be used if the MLP is trained in the same process that uses the MLP for evaluation with evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpEvaluateClassMlp or for classification with classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpClassifyClassMlp. In this case, the memory required for the training samples can be freed with clear_samples_class_mlpclear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlpClearSamplesClassMlp, and hence memory can be saved. In the normal usage, in which the MLP is trained offline and written to a file with write_class_mlpwrite_class_mlpWriteClassMlpWriteClassMlpWriteClassMlp, it is typically unnecessary to call clear_samples_class_mlpclear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlpClearSamplesClassMlp because write_class_mlpwrite_class_mlpWriteClassMlpWriteClassMlpWriteClassMlp does not save the training samples, and hence the online process, which reads the MLP with read_class_mlpread_class_mlpReadClassMlpReadClassMlpReadClassMlp, 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

MLPHandleMLPHandleMLPHandleMLPHandleMLPHandle (input_control, state is modified)  class_mlp(-array) HClassMlp, HTupleHTupleHtuple (integer) (IntPtr) (Hlong) (Hlong)

MLP handle.

Result

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

Possible Predecessors

train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlp, write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlp

See also

create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlp, clear_class_mlpclear_class_mlpClearClassMlpClearClassMlpClearClassMlp, add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlpAddSampleClassMlp, read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpReadSamplesClassMlp

Module

Foundation


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