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  Tutorial: FEED FORWARD NEURAL NETWORKS - A JAVA IMPLEMENTATION v2.0

This is a java implementation of some types of feed forward neural networks. You can simulate multilayer perceptron nets, generalized feed forward nets, modular feed forward nets using this package.

Tutorial Details:

What can you do with it?
You can:
- Build multilayer perceptron, generalized feed forward, modular feed forward nets;
- Train your net using batch, mini batch and incremental training;
- Create pattern sets out of semicolon separated files, train the net using these patterns,
- Spare some of the patterns for cross validation and testing, calculate error terms out of these patterns;
- Load and save network configuration and weights;
- Use logistic, tanh and linear activation functions;
- Use momentum;
- Determine the flatness of the activation functions;
- Use different momentum rate, flatness, learning rates for each neuron.


 

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FEED FORWARD NEURAL NETWORKS - A JAVA IMPLEMENTATION v2.0

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FEED FORWARD NEURAL NETWORKS - A JAVA IMPLEMENTATION v2.0

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