Download JAR files tagged by holmes with all dependencies

Holmes is a library that provides a simple and fluent API for writing business rules validations on Java projects.

Classifier for incremental learning of large datasets by way of racing logit-boosted committees. For more information see: Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall: Racing committees for large datasets. In: Proceedings of the 5th International Conferenceon Discovery Science, 153-164, 2002.

This package provides four search methods for attribute selection: ExhaustiveSearch, GeneticSearch, RandomSearch and RankSearch. See: David E. Goldberg (1989). Genetic algorithms in search, optimization and machine learning. Addison-Wesley. Mark Hall, Geoffrey Holmes (2003). Benchmarking attribute selection techniques for discrete class data mining. IEEE Transactions on Knowledge and Data Engineering. 15(6):1437-1447.

Binary-class and multi-class alternating decision trees. For more information see: Freund, Y., Mason, L.: The alternating decision tree learning algorithm. In: Proceeding of the Sixteenth International Conference on Machine Learning, Bled, Slovenia, 124-133, 1999. Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark Hall: Multiclass alternating decision trees. In: ECML, 161-172, 2001.

Interactively classify through visual means. You are Presented with a scatter graph of the data against two user selectable attributes, as well as a view of the decision tree. You can create binary splits by creating polygons around data plotted on the scatter graph, as well as by allowing another classifier to take over at points in the decision tree should you see fit. For more information see: Malcolm Ware, Eibe Frank, Geoffrey Holmes, Mark Hall, Ian H. Witten (2001). Interactive machine learning: letting users build classifiers. Int. J. Hum.-Comput. Stud. 55(3):281-292.