Software Last updated: Jan 2009Magnum Opus is commercial association discovery software that implements many of my association discovery techniques. A free, highly functional, demo version is also available, see free association discovery software. OPUS Miner is an open source implementation of the OPUS Miner algorithm which applies OPUS search for Filtered Top-k Association Discovery of Self-Sufficient Itemsets, as described in the following papers. Webb, G.I. (2011). Filtered-top-k Association Discovery. WIREs Data Mining and Knowledge Discovery 1(3). Wiley, pages 183-192. [Pre-Publication PDF] [Link to paper via Wiley Online Library] Webb, G.I. (2010). Self-Sufficient Itemsets: An Approach to Screening Potentially Interesting Associations Between Items. Transactions on Knowledge Discovery from Data 4. ACM, pages 3:1-3:20. [Link to paper via ACM Digital Library] Webb, G.I. (2008). Layered Critical Values: A Powerful Direct-Adjustment Approach to Discovering Significant Patterns. Machine Learning 71(2-3). Netherlands: Springer, pages 307-323 [Technical Note]. [Link to paper via Springerlink.] Webb, G.I. (2007). Discovering Significant Patterns. Machine Learning 68(1). Netherlands: Springer, pages 1-33. [Link to paper via Springerlink] The Knowledge Factory is an expert system development environment that incorporates interactive rule induction. The Knowledge Factory works with you to produce and refine expert systems. C4.5X is
a set of files that extends C4.5 release 6 to incorporate the postprocessing described in:
Cover is an attribute-value machine learning system that employs the OPUS algorithm for complete search. The principles by which Cover operates are described in the OPUS series of papers. We have submitted numerous systems for inclusion in releases of the Weka machine learning workbench. These include: AODE: averaged one-dependence estimators, an efficient technique for lessening the attribute-independence assumption of naive Bayes. [papers] LBR: lazy Bayesian rules, a lazy learning approach to lessening the attribute-independence assumption of naive Bayes. [papers] PKID: proportional k-interval discretization, a discretization technique for naive Bayes. [papers] MultiBoosting: an ensemble learning technique that combines boosting and bagging, attaining much of the former's superior bias reduction together with much of the latter's superior variance reduction. [papers] Bias-Variance: Bias-variance decomposition using the sub-sampled cross-validation procedure. [paper] OPUS: a branch and bound search algorithm that enables efficient admissible search through spaces for which the order of search operator application is not significant. [papers] BUG REPORTS: All the software is developed for research purposes. Some bugs may be present within the software. We would appreciate any comments, bug descriptions or suggestions regarding the software. Please e-mail with your reports. |