read_samples_class_mlp — 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 added to 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, the operators read_samples_class_mlp, add_sample_class_mlp, and write_samples_class_mlp 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 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.
This operator modifies the state of the following input parameter:
If the parameters are valid, the operator read_samples_class_mlp returns the value 2 (H_MSG_TRUE). If necessary, an exception is raised.