The focus of this project is to build a a new Bayesian Classification algorithm for mining molecular biology data sets. A very important application of data mining is Bioinformatics, where the goal is to discover interesting knowledge from molecular biology data sets. Classification is one of the major tasks of data mining, and Bayesian algorithms are a paradigm of classification algorithms based on probability theory. The approach being use to build a Bayesian classifier is inspired on Ant Colony algorithms; Essentially they are systems based on agents that simulate the behaviour of natural ants, including mechanisms of cooperation and adaptation. Further testing of this experiment is needed to confirm the findings and final outcome of the project. Developed by jr239@kent.ac.uk Miraculously supervised by Dr Alex A. Freitas
Source and ready to run files at jr239co620
