GETTING STARTED

This page contains tutorials, tools and techniques that people in the area of ML, IR and UM have found useful for their research.

If you feel that anything is missing and should be listed here, or if you have general comments, feedback, corrections, etc., please let us know!.

Tools:

• ML specific:
  • RIPPER, a rule-learning system available for research purposes. Written by William Cohen.
  • Rainbow machine learning package. Nice integrated toolkit with multiple learning algorithms available. Written by Andrew McCallum and students while he was at CMU.
  • C4.5, a decision-tree learner. Written by Ross Quinlan.
  • SVM^light, a fast Support Vector Machine implementation. Written by Thorsten Joachims.
  • (C-)Progol, a first order rule learner based on inverese entailment. Written by Stephen Muggleton.
  • FOIL, an information-gain guided top-down first-order rule induction system. Also written by Ross Quinlan.
  • (P-)Progol & Aleph, two further first order ILP rule learner in the tradition of Progol and GOLEM. Written by Ashwin Srinivasan.

Tutorials:

Techniques:

Page Last Modified: Tue Jul 8 10:27:31 2003

Created by: Sofus A. Macskassy

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