MultiLayerPerceptron consists of a MATLAB class including a configurable multi-layer perceptron (or
feedforward neural network) and the methods useful for its setting and its training.
The multi-layer perceptron is fully configurable by the user through the definition of lengths and activation
functions of its successive layers as follows:
- Random initialization of weights and biases through a dedicated method,
- Setting of activation functions through method "set".
The training method of the neural network is based on the following algorithms:
- Gradient descent, with configurable learning rate, momentum and size of batches,
- Levenberg-Marquardt, with configurable parameters and an optional bayesian regularization.
The evolution of the training is viewable through an embedded visualization window and configurable in
- Minimum mean square error (MSE),
- Number of epochs,
- Ratio between training and validation data sets.
Eric Ogier (2023). Multi-layer perceptron (https://www.mathworks.com/matlabcentral/fileexchange/69762-multi-layer-perceptron), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
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