Holmes, G. & Hall, M.A. (2000). Correlation-based feature selection of discrete and numeric class machine learning. (Working paper 00/09). Hamilton, New Zealand: University of Waikato, Department of Computer Science.
Permanent Research Commons link: https://hdl.handle.net/10289/1025
WEKA (Waikato Environment for Knowledge Analysis) is a comprehensive suite of Java class libraries that implement many state-of-the-art machine learning/data mining algorithms. Non-programmers interact with the software via a user interface component called the Knowledge Explorer. Applications constructed from the WEKA class libraries can be run on any computer with a web browsing capability, allowing users to apply machine learning techniques to their own data regardless of computer platform. This paper describes the user interface component of the WEKA system in reference to previous applications in the predictive modeling of foods.
University of Waikato, Department of Computer Science
- 2000 Working Papers