Genetic algorithms are a particular class of algorithms that provide an approach to learning inspired by the model of biological evolution, i.e. selection, crossover and mutation. The goal of this project was to implement a genetic algorithm including different crossover rules. Two standard UCI data sets were given, to evaluate the performance of the implementation. WEKA has been chosen as a framework to facilitate the development.
The project report can be downloaded here.
genee is 100% open-source and free! Download it and play around with it. If you're interested to join the project, drop me an email.
More information can be found inside the orcus-genee package, which can be downloaded here.