Name
read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlp — Read the training data of a multilayer perceptron from a file.
read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlp reads training samples from the file
given by FileNameFileNameFileNameFileNameFileNamefileName and adds them to the training samples
that have already been added to the multilayer perceptron (MLP)
given by MLPHandleMLPHandleMLPHandleMLPHandleMLPHandleMLPHandle. The MLP must be created with
create_class_mlpcreate_class_mlpCreateClassMlpcreate_class_mlpCreateClassMlpCreateClassMlp before calling
read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlp. As described with
train_class_mlptrain_class_mlpTrainClassMlptrain_class_mlpTrainClassMlpTrainClassMlp and write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlp, the
operators read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlp,
add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlp, and write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlp
can be used to build up a extensive set of training samples, and
hence to improve the performance of the MLP by retraining the MLP
with extended data sets.
It should be noted that the training samples must have the correct
dimensionality. The feature vectors and target vectors stored in
FileNameFileNameFileNameFileNameFileNamefileName must have the lengths NumInput and
NumOutput that were specified with
create_class_mlpcreate_class_mlpCreateClassMlpcreate_class_mlpCreateClassMlpCreateClassMlp. If this is not the case an error message
is returned.
- 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:
The value of this parameter may not be shared across multiple threads without external synchronization.
If the parameters are valid, the operator
read_samples_class_mlpread_samples_class_mlpReadSamplesClassMlpread_samples_class_mlpReadSamplesClassMlpReadSamplesClassMlp returns the value 2 (H_MSG_TRUE). If necessary,
an exception is raised.
create_class_mlpcreate_class_mlpCreateClassMlpcreate_class_mlpCreateClassMlpCreateClassMlp
train_class_mlptrain_class_mlpTrainClassMlptrain_class_mlpTrainClassMlpTrainClassMlp
add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlp
write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlp,
clear_samples_class_mlpclear_samples_class_mlpClearSamplesClassMlpclear_samples_class_mlpClearSamplesClassMlpClearSamplesClassMlp
Foundation