Mark Hall
Mark Hall
Honorary Research Associate, University of Waikato, New Zealand
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Data mining: practical machine learning tools and techniques with Java implementations
IH Witten, E Frank
Acm Sigmod Record 31 (1), 76-77, 2002
The WEKA data mining software: an update
M Hall, E Frank, G Holmes, B Pfahringer, P Reutemann, IH Witten
ACM SIGKDD explorations newsletter 11 (1), 10-18, 2009
Correlation-based feature selection for machine learning
MA Hall
University of Waikato, 1999
Data mining and knowledge discovery handbook
O Maimon, L Rokach
Springer 2 (2005), 2005
Correlation-based feature selection of discrete and numeric class machine learning
MA Hall
University of Waikato, Department of Computer Science, 2000
Data Mining Practical Machine Learning Tools and Techniques Third Edition
IH Witten, E Frank, MA Hall
Morgan Kaufmann, 2017
Logistic model trees
N Landwehr, M Hall, E Frank
Machine learning 59 (1-2), 161-205, 2005
Benchmarking attribute selection techniques for discrete class data mining
MA Hall, G Holmes
IEEE Transactions on Knowledge and Data engineering 15 (6), 1437-1447, 2003
Correlation-based feature subset selection for machine learning
MA Hall
Thesis submitted in partial fulfillment of the requirements of the degree of …, 1998
Data mining: Practical machine learning tools and techniques
HW Ian, F Eibe
Morgan Kaufmann Publishers, 2005
The WEKA workbench
E Frank, MA Hall, IH Witten
Morgan Kaufmann, 2016
Practical machine learning tools and techniques
IH Witten, E Frank, MA Hall, CJ Pal
Morgan Kaufmann, 578, 2005
Data mining in bioinformatics using Weka
E Frank, M Hall, L Trigg, G Holmes, IH Witten
Bioinformatics 20 (15), 2479-2481, 2004
Flow clustering using machine learning techniques
A McGregor, M Hall, P Lorier, J Brunskill
International workshop on passive and active network measurement, 205-214, 2004
Feature Selection for Machine Learning: Comparing a Correlation-Based Filter Approach to the Wrapper.
MA Hall, LA Smith
FLAIRS conference 1999, 235-239, 1999
A simple approach to ordinal classification
E Frank, M Hall
European Conference on Machine Learning, 145-156, 2001
Practical feature subset selection for machine learning
MA Hall, LA Smith
Springer 20, 181-191, 1998
Gene selection from microarray data for cancer classification—a machine learning approach
Y Wang, IV Tetko, MA Hall, E Frank, A Facius, KFX Mayer, HW Mewes
Computational biology and chemistry 29 (1), 37-46, 2005
Weka manual for version 3-6-0
RR Bouckaert, E Frank, M Hall, R Kirkby, P Reutemann, A Seewald, ...
University of Waikato, Hamilton, New Zealand 2, 2008
Locally weighted naive bayes
E Frank, M Hall, B Pfahringer
arXiv preprint arXiv:1212.2487, 2012
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