Implementation of Radial Basis Function (RBF) Neural Network, with moving centers, in java.
- help me to internalize the mathematical description of the algorithm.
- understand the algorithm intimately and discover parameter configurations.
- how the parameters of the algorithm influence its performance.
- experiment with various datasets and see the behaviour of the algorithm.
- track performance of the algorithm-implementation with different metrics.
- light preprocessing of dataset.
- explore opportunities to make the implementation more efficient.
The following parameters of the network can be set by a text file, its path given as command line argument:
- number of centres - hidden neurons
- number of input neurons
- number of output neurons
- learning rate
- standard deviation (sigma)
- number of iterations
- initial coordinates of the centres
javac -d ./bin ./src/io/github/ghadj/rbfneuralnetwork/*.java
java -cp ./bin io.github.ghadj.rbfneuralnetwork.RBFNNDriver <path to parameters' file>