Flexible Decision Trees in a General Data-Mining Environment

J. W. Comley, L. Allison and L. J. Fitzgibbon, Fourth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL-2003), Hong Kong, 21-23 March 2003

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Abstract. We describe a new data-mining platform, CDMS, aimed at the streamlined development, comparison and application of machine learning tools. We discuss its type system, focussing on the treatment of statistical models as first-class values.

This allows rapid construction of composite models - complex models built from simpler ones - such as mixture models, Bayesian networks and decision trees. We illustrate this with a flexible decision tree tool for CDMS which rather than being limited to discrete target attributes, can model any kind of data using arbitrary probability distributions.

[preprint.pdf], [springer][12/'03].

Coding Ockham's Razor, L. Allison, Springer

A Practical Introduction to Denotational Semantics, L. Allison, CUP

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© L. Allison   http://www.allisons.org/ll/   (or as otherwise indicated),
Faculty of Information Technology (Clayton), Monash University, Australia 3800 (6/'05 was School of Computer Science and Software Engineering, Fac. Info. Tech., Monash University,
was Department of Computer Science, Fac. Comp. & Info. Tech., '89 was Department of Computer Science, Fac. Sci., '68-'71 was Department of Information Science, Fac. Sci.)
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