Multi-layer perceptron
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
terms of:
- Minimum mean square error (MSE),
- Number of epochs,
- Ratio between training and validation data sets.
Video demonstrations:
Citar como
Eric Ogier (2024). Multi-layer perceptron (https://www.mathworks.com/matlabcentral/fileexchange/69762-multi-layer-perceptron), MATLAB Central File Exchange. Recuperado .
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- AI, Data Science, and Statistics > Deep Learning Toolbox > Function Approximation, Clustering, and Control > Function Approximation and Clustering > Define Shallow Neural Network Architectures >
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MultiLayerPerceptron
MultiLayerPerceptron
Versión | Publicado | Notas de la versión | |
---|---|---|---|
1.0.0.0 |