YALE
From Wikipedia, the free encyclopedia
- For other uses of Yale, see Yale (disambiguation).
YALE ("Yet Another Learning Environment") is an environment for machine learning experiments and data mining. Experiments can be made up of a large number of arbitrarily nestable operators and their setup is described by XML files which can easily be created with a graphical user interface. Applications of YALE cover both research and real-world data mining tasks.
It has been developed by the Artificial Intelligence Unit of the University of Dortmund since 2001. Its license is GNU and since 2004 it is now hosted by SourceForge.
YALE provides more than 350 operators for all main machine learning procedures including input and output, data preprocessing and visualization. It is written in Java and therefore able to work in all major operating systems. It also integrates all learning schemes and attribute evaluators of the Weka learning environment.
[edit] Properties
Some properties of YALE are:
- written in Java
- Knowledge Discovery processes are modeled as operator trees
- internal XML representation ensures standardized interchange format of data mining experiments
- scripting language allows for automatic large-scale experiments
- multi-layered data view concept ensures efficient and transparent data handling
- graphical user interface, command line mode (batch mode), and Java API for using YALE from your own programs
- plugin and extension mechanisms, several plugins already exist
- plotting facility offering a large set of high-dimensional visualization schemes for data and models
- applications include text mining, multimedia mining, feature engineering, data stream mining and tracking drifting concepts, development of ensemble methods, and distributed data mining.
[edit] Further reading
- Mierswa, Ingo and Wurst, Michael and Klinkenberg, Ralf and Scholz, Martin and Euler, Timm: YALE: Rapid Prototyping for Complex Data Mining Tasks, in Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-06), 2006.
