ClassesClasses | | Operators

write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlp (Operator)

Name

write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlp — Write the training data of a multilayer perceptron to a file.

Signature

write_samples_class_mlp( : : MLPHandle, FileName : )

Herror write_samples_class_mlp(const Hlong MLPHandle, const char* FileName)

Herror T_write_samples_class_mlp(const Htuple MLPHandle, const Htuple FileName)

void WriteSamplesClassMlp(const HTuple& MLPHandle, const HTuple& FileName)

void HClassMlp::WriteSamplesClassMlp(const HString& FileName) const

void HClassMlp::WriteSamplesClassMlp(const char* FileName) const

static void HOperatorSet.WriteSamplesClassMlp(HTuple MLPHandle, HTuple fileName)

void HClassMlp.WriteSamplesClassMlp(string fileName)

Description

write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlp writes the training samples stored in the multilayer perceptron (MLP) MLPHandleMLPHandleMLPHandleMLPHandleMLPHandle to the file given by FileNameFileNameFileNameFileNamefileName. write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlp can be used to build up a database of training samples, and hence to improve the performance of the MLP by training it with an extended data set (see train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlp). For other possible uses of write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlp see get_prep_info_class_mlpget_prep_info_class_mlpGetPrepInfoClassMlpGetPrepInfoClassMlpGetPrepInfoClassMlp.

The file FileNameFileNameFileNameFileNamefileName is overwritten by write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlp. Nevertheless, extending the database of training samples is easy to do because read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpReadSamplesClassMlp and add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlpAddSampleClassMlp add the training samples to the training samples that are already stored in memory with the MLP.

Execution Information

Parameters

MLPHandleMLPHandleMLPHandleMLPHandleMLPHandle (input_control)  class_mlp HClassMlp, HTupleHTupleHtuple (integer) (IntPtr) (Hlong) (Hlong)

MLP handle.

FileNameFileNameFileNameFileNamefileName (input_control)  filename.write HTupleHTupleHtuple (string) (string) (HString) (char*)

File name.

Result

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

Possible Predecessors

add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlpAddSampleClassMlp

Possible Successors

clear_samples_class_mlpclear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlpClearSamplesClassMlp

See also

create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlp, get_prep_info_class_mlpget_prep_info_class_mlpGetPrepInfoClassMlpGetPrepInfoClassMlpGetPrepInfoClassMlp, read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlpReadSamplesClassMlp

Module

Foundation


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