Pointers: http://www.ics.uci.edu/~mlearn/Hydra.html
Code:Common Lisp
References:Ali and Pazzani 1993

The relational concept learner HYDRA extends the machine learning program FOCL by adding likelihood ratios to the induced classification rules. HYDRA learns a concept description for each class. The concept descriptions compete to classify test examples based on the likelihood ratios that are assigned to clauses of that concept description. This makes the algorithm more robust against noise.


  1. K.M. Ali and M.J. Pazzani. Hydra: A noise-tolerant relational concept learning algorithm. In R. Bajcsy, editor, Proceedings of the 13th International Joint Conference on Artificial Intelligence, pages 1064-1071. Morgan Kaufmann, 1993.

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