Mark Hall
Mark Hall
Honorary Research Associate, University of Waikato, New Zealand
Verified email at cs.waikato.ac.nz
TitleCited byYear
Data mining: practical machine learning tools and techniques with Java implementations
IH Witten, E Frank
Acm Sigmod Record 31 (1), 76-77, 2002
389782002
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
200422009
Correlation-based feature selection for machine learning
MA Hall
University of Waikato, 1999
33441999
Data mining and knowledge discovery handbook
O Maimon, L Rokach
springer 2 (2005), 2005
2644*2005
Correlation-based feature selection of discrete and numeric class machine learning
MA Hall
University of Waikato, Department of Computer Science, 2000
18842000
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
12962003
Logistic model trees
N Landwehr, M Hall, E Frank
Machine learning 59 (1-2), 161-205, 2005
12542005
Correlation-based feature subset selection for machine learning
MA Hall
Thesis submitted in partial fulfillment of the requirements of the degree of …, 1998
11131998
Data mining in bioinformatics using Weka
E Frank, M Hall, L Trigg, G Holmes, IH Witten
Bioinformatics 20 (15), 2479-2481, 2004
8852004
Data Mining: Practical Machine Learning Tools and Techniques.
Y Zhang, D Lv, R Guo, TG Dietterich, ZH Zhou, C Zhang, Y Ma, ...
Journal of Software Engineering 11 (1), 97-136, 1997
854*1997
The WEKA workbench
E Frank, MA Hall, IH Witten
Morgan Kaufmann, 2016
7712016
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
6572004
Feature selection for machine learning: comparing a correlation-based filter approach to the wrapper.
MA Hall, LA Smith
FLAIRS conference 1999, 235-239, 1999
5321999
Practical feature subset selection for machine learning
MA Hall, LA Smith
Springer 20, 181-191, 1998
4741998
A simple approach to ordinal classification
E Frank, M Hall
European Conference on Machine Learning, 145-156, 2001
4612001
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
3962005
WEKA Manual for Version 3-6-1
RR Bouckaert, E Frank, M Hall, R Kirkby, P Reutemann, A Seewald, ...
The University of Waikato: Hamilton, New Zealand, 2009
394*2009
Practical machine learning tools and techniques
IH Witten, E Frank, MA Hall
Morgan Kaufmann, 578, 2005
366*2005
Locally weighted naive bayes
E Frank, M Hall, B Pfahringer
Proceedings of the Nineteenth conference on Uncertainty in Artificial …, 2002
3632002
Chest pain: relationship of psychiatric illness to coronary arteriographic results
W Katon, ML Hall, J Russo, L Cormier, M Hollifield, PP Vitaliano, ...
The American journal of medicine 84 (1), 1-9, 1988
3591988
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Articles 1–20