Read the training data of a multilayer perceptron from a file.

read_samples_class_mlp reads training samples from the file given by FileName and adds them to the training samples that have already been stored in the multilayer perceptron (MLP) given by MLPHandle. The MLP must be created with create_class_mlp before calling read_samples_class_mlp. As described with train_class_mlp and write_samples_class_mlp, read_samples_class_mlp, add_sample_class_mlp, and write_samples_class_mlp can be used to build up a database 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 FileName must have the lengths NumInput and NumOutput that were specified with create_class_mlp. If this is not the case an error message is returned.

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

read_samples_class_mlp is processed completely exclusively without parallelization.

create_class_mlp

train_class_mlp

add_sample_class_mlp

write_samples_class_mlp, clear_samples_class_mlp

Foundation