RBF-Neural-Network

Implementation of Radial Basis Function (RBF) Neural Network, with moving centers, in java.

Objectives

• 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.

Implementation

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

Compile & Run

javac -d ./bin ./src/io/github/ghadj/rbfneuralnetwork/*.java

java -cp ./bin io.github.ghadj.rbfneuralnetwork.RBFNNDriver <path to parameters' file>