Taylor, Charles C. - School of Mathematics, University of Leeds

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Taylor, Charles C. - School of Mathematics, University of Leeds

Machine Learning of Rules and Trees C. Feng (1) and D. Michie (2)
Machine Learning, Neural and Statistical Classification
Knowledge Representation Claude Sammut
Local polynomial regression for circular predictors Marco Di Marzioa
Machine Learning, Neural and Statistical Classification
Methods for Comparison R. J. Henery
Dataset Descriptions and Results Various StatLog partners
Classical Statistical Methods J. M. O. Mitchell
Machine Learning, Neural and Statistical Classification
Analysis of Results P. B. Brazdil (1) and R. J. Henery (2)
Protein Bioinformatics and Mixtures of Bivariate von Mises Distributions for Angular Data
Review of Previous Empirical Comparisons R. J. Henery
Introduction D. Michie (1), D. J. Spiegelhalter (2) and C. C. Taylor (3)
Learning to Control Dynamic Systems Tanja Urbancic (1) and Ivan Bratko (1,2)
Conclusions D. Michie (1), D. J. Spiegelhalter (2) and C. C.Taylor (3)
Boosting Kernel Density Estimates: a Bias Reduction Marco Di Marzio
Kernel Density Classification and Boosting: an L2 analysis M. Di Marzio (dimarzio@dmqte.unich.it)
On boosting kernel regression Marco Di Marzio and Charles C. Taylor
Automatic Bandwidth Selection for Circular Density Charles C. Taylor
October 21, 2008 8:42 Journal of Nonparametric Statistics jnsrev3 Journal of Nonparametric Statistics
Classification R. J. Henery
A Dataset availability The ``public domain'' datasets are listed below with an anonymous ftp address. If you do
Neural Networks R. Rohwer (1), M. WynneJones (1) and F. Wysotzki (2)
Modern Statistical Techniques R. Molina (1), N. Perez de la Blanca (1) and C. C. Taylor (2)