Classification - Neural Nets🔗
Operators🔗
add_class_train_data_mlp: Add training data to a multilayer perceptron (MLP).
add_sample_class_mlp: Add a training sample to the training data of a multilayer
perceptron.
classify_class_mlp: Calculate the class of a feature vector by a multilayer perceptron.
clear_class_mlp: Clear a multilayer perceptron.
clear_samples_class_mlp: Clear the training data of a multilayer perceptron.
create_class_mlp: Create a multilayer perceptron for classification or regression.
deserialize_class_mlp: Deserialize a serialized multilayer perceptron.
evaluate_class_mlp: Calculate the evaluation of a feature vector by a multilayer
perceptron.
get_class_train_data_mlp: Get the training data of a multilayer perceptron (MLP).
get_params_class_mlp: Return the parameters of a multilayer perceptron.
get_prep_info_class_mlp: Compute the information content of the preprocessed feature vectors
of a multilayer perceptron.
get_regularization_params_class_mlp: Return the regularization parameters of a multilayer perceptron.
get_rejection_params_class_mlp: Get the parameters of a rejection class.
get_sample_class_mlp: Return a training sample from the training data of a multilayer
perceptron.
get_sample_num_class_mlp: Return the number of training samples stored in the training data of
a multilayer perceptron.
read_class_mlp: Read a multilayer perceptron from a file.
read_samples_class_mlp: Read the training data of a multilayer perceptron from a file.
select_feature_set_mlp: Selects an optimal combination of features to classify the provided data.
serialize_class_mlp: Serialize a multilayer perceptron (MLP).
set_regularization_params_class_mlp: Set the regularization parameters of a multilayer perceptron.
set_rejection_params_class_mlp: Set the parameters of a rejection class.
train_class_mlp: Train a multilayer perceptron.
write_class_mlp: Write a multilayer perceptron to a file.
write_samples_class_mlp: Write the training data of a multilayer perceptron to a file.