Mark Hall
Mark Hall
Honorary Research Associate, University of Waikato, New Zealand
Zweryfikowany adres z cs.waikato.ac.nz
Cytowane przez
Cytowane przez
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
The University of Waikato, 1999
Practical machine learning tools and techniques
IH Witten, E Frank, MA Hall, CJ Pal, M Data
Data mining 2 (4), 403-413, 2005
Correlation-based feature selection of discrete and numeric class machine learning
MA Hall
University of Waikato, Department of Computer Science, 2000
The WEKA workbench
E Frank, MA Hall, IH Witten
Morgan Kaufmann, 2016
Logistic model trees
N Landwehr, M Hall, E Frank
Machine learning 59, 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 fulfilment of the requirements of the degree of …, 1988
Data mining in bioinformatics using Weka
E Frank, M Hall, L Trigg, G Holmes, IH Witten
Bioinformatics 20 (15), 2479-2481, 2004
The WEKA data mining software: an update, SIGKDD Explor
M Hall, E Frank, G Holmes, B Pfahringer, P Reutemann, IH Witten
Newsl 11 (1), 10-18, 2009
Feature selection for machine learning: comparing a correlation-based filter approach to the wrapper
MA Hall, LA Smith
Proceedings of the twelfth international Florida artificial intelligence …, 1999
Flow clustering using machine learning techniques
A McGregor, M Hall, P Lorier, J Brunskill
Passive and Active Network Measurement: 5th International Workshop, PAM 2004 …, 2004
Weka-a machine learning workbench for data mining
E Frank, M Hall, G Holmes, R Kirkby, B Pfahringer, IH Witten, L Trigg
Data mining and knowledge discovery handbook, 1269-1277, 2010
A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form
HL O’Brien, P Cairns, M Hall
International Journal of Human-Computer Studies 112, 28-39, 2018
A simple approach to ordinal classification
E Frank, M Hall
Machine Learning: ECML 2001: 12th European Conference on Machine Learning …, 2001
Practical feature subset selection for machine learning
MA Hall, LA Smith
Springer 20, 181-191, 1998
Data mining: practical machine learning tools and techniques
E Frank, MA Hall
Morgan Kaufmann, 2011
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 3-9-1
RR Bouckaert, E Frank, M Hall, R Kirkby, P Reutemann, A Seewald, ...
University of Waikato: Hamilton, New Zealand, 1-341, 2016
Locally weighted naive bayes
E Frank, M Hall, B Pfahringer
arXiv preprint arXiv:1212.2487, 2012
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