On the Methodology for Comparing Learning Algorithms: A Case Study

Bradley, Andrew P., Lovell, Brian C., Ray, Michael and Hawson, Geoffrey (1994). On the Methodology for Comparing Learning Algorithms: A Case Study. In: Australian and New Zealand Conference on Intelligent Information Systems (ANZIIS'94), Brisbane, Australia, (37-41). November, 1994.

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Author Bradley, Andrew P.
Lovell, Brian C.
Ray, Michael
Hawson, Geoffrey
Title of paper On the Methodology for Comparing Learning Algorithms: A Case Study
Conference name Australian and New Zealand Conference on Intelligent Information Systems (ANZIIS'94)
Conference location Brisbane, Australia
Conference dates November, 1994
Journal name Australian and New Zealand Conference on Intelligent Information Systems - Proceedings
Publication Year 1994
Sub-type Fully published paper
Start page 37
End page 41
Total pages 5
Abstract/Summary In this paper we explore several issues relevant to the benchmarking and comparison of machine learning algorithms. We illustrate those issues in case study using the decision tree induction algorithm C4.5 and multiscale classification (MSC), multi-variable regression (MVR). Then for a 'real world' problem we compare estimates of the true error rates for each classifier, first on a single train and test partition, and then using cross validated sub-sampling technique. The relevance of the test is then discussed in relation to comparing the classifier accuracies. The paper concludes by evaluating the performance of these four fundamentally different approaches to the solution of the regression problem.
Subjects 280000 Information, Computing and Communication Sciences
Keyword iris-research
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Unknown

 
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Created: Wed, 04 Feb 2004, 10:00:00 EST by Brian C. Lovell