clear_samples_class_mlpT_clear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlp (Operator)

Name

clear_samples_class_mlpT_clear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlp — Clear the training data of a multilayer perceptron.

Signature

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

• 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:

• MLPHandleMLPHandleMLPHandleMLPHandleMLPHandle

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

Parameters

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