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Description

2 data files: -- horse-colic.data: 300 training instances -- horse-colic.test: 68 test instances Possible class attributes: 24 (whether lesion is surgical) -- others include: 23, 25, 26, and 27 Many Data types: (continuous, discrete, and nominal)

Related Papers

• Eibe Frank and Ian H. Witten. Generating Accurate Rule Sets Without Global Optimization. ICML. 1998. [link]
• Huan Liu and Hiroshi Motoda and Lei Yu. Feature Selection with Selective Sampling. ICML. 2002. [link]
• Kai Ming Ting and Ian H. Witten. Stacked Generalization: when does it work. Department of Computer Science University of Waikato. [link]
• Alexander K. Seewald. Dissertation Towards Understanding Stacking Studies of a General Ensemble Learning Scheme ausgefuhrt zum Zwecke der Erlangung des akademischen Grades eines Doktors der technischen Naturwissenschaften. [link]
• James J. Liu and James Tin and Yau Kwok. An Extended Genetic Rule Induction Algorithm. Department of Computer Science Wuhan University. [link]
• H. Altay G uvenir and Aynur Akkus. WEIGHTED K NEAREST NEIGHBOR CLASSIFICATION ON FEATURE PROJECTIONS. Department of Computer Engineering and Information Science Bilkent University. [link]
• Gabor Melli. A Lazy Model-Based Approach to On-Line Classification. University of British Columbia. 1989. [link]
• Marc Sebban and Richard Nock and Stphane Lallich. Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem. Journal of Machine Learning Research, 3. 2002. [link]
• Kai Ming Ting and Ian H. Witten. Issues in Stacked Generalization. J. Artif. Intell. Res. (JAIR, 10. 1999. [link]
• Mukund Deshpande and George Karypis. Using conjunction of attribute values for classification. CIKM. 2002. [link]
• Julie Greensmith. New Frontiers For An Artificial Immune System. Digital Media Systems Laboratory HP Laboratories Bristol. 2003. [link]
• Richard Nock and Marc Sebban and David Bernard. A SIMPLE LOCALLY ADAPTIVE NEAREST NEIGHBOR RULE WITH APPLICATION TO POLLUTION FORECASTING. International Journal of Pattern Recognition and Artificial Intelligence Vol. 2003. [link]
• Mark A. Hall. Department of Computer Science Hamilton, NewZealand Correlation-based Feature Selection for Machine Learning. Doctor of Philosophy at The University of Waikato. 1999. [link]