This document provides an overview of the various documents and links that are part of this project's general information. All of this content is automatically generated by Maven on behalf of the project.
| Document | Description |
|---|---|
| About | 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 |
| Continuous Integration | This is a link to the definitions of all continuous integration processes that builds and tests code on a frequent, regular basis. |
| Dependencies | This document lists the projects dependencies and provides information on each dependency. |
| Issue Tracking | This is a link to the issue management system for this project. Issues (bugs, features, change requests) can be created and queried using this link. |
| Mailing Lists | This document provides subscription and archive information for this project's mailing lists. |
| Project License | This is a link to the definitions of project licenses. |
| Project Summary | This document lists other related information of this project |
| Project Team | This document provides information on the members of this project. These are the individuals who have contributed to the project in one form or another. |
| Source Repository | This is a link to the online source repository that can be viewed via a web browser. |
