Machine Learning and Statistics: The Interface
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More About This Title Machine Learning and Statistics: The Interface

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About the editors

G. Nakhaeizadeh is Senior Scientist at the Daimler-Benz Research Center in Ulm, Germany, and Professor at Karlsruhe University. From 1990 to 1993 he directed the Machine Learning Project StatLog, which was supported by the European Union. His research interests center on symbolic and statistical learning and their industrial and commercial applications.

C. C. Taylor is Senior Lecturer in the Department of Statistics at the University of Leeds, U.K. His particular interests include nonparametric density estimation methods related to classification and statistical methods in image analysis.

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Partial table of contents:

The Decision-Tree Algorithm CAL5 Based on a Statistical Approach to Its Splitting Algorithm (W. &Muml;uller & F. Wysotzki).

Probabilistic Symbolic Classifiers: An Empirical Comparison from a Statistical Perspective (M. Chiogna).

Quality of Decision Rules: Definitions and Classification Schemes for Multiple Rules (I. Bruha).

Distance-Based Decision Trees (C. Taylor).

Combining Statistical Techniques and Search Heuristics to Perform Effective Feature Selection (M. Richeldi & M. Rossotto).

Comparison of Three Inductive Numerical Law Discovery Systems (M. Moulet).

Analogy as Minimization of Description Length (A. Cornuejols).

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