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Discovering statistically non-redundant subgroups
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DOI：10.1016/j.knosys.2014.04.030.png)
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Abstract
En 中文
The objective of subgroup discovery is to find groups of individuals who are statistically different from others in a large data set. Most existing measures of the quality of subgroups are intuitive and do not precisely capture statistical differences of a group with the other, and their discovered results contain many redundant subgroups. Odds ratio is a statistically sound measure to quantify the statistical difference of two groups for a certain outcome and it is a very suitable measure for quantifying the quality of subgroups. In this paper, we propose a statistically sound framework for statistically non-redundant subgroup discovery: measuring the quality of subgroups by the odds ratio and defining statistically non-redundant subgroups by the error bounds of odds ratios. We show that our proposed method is faster than most existing methods and discovers complete statistically non-redundant subgroups. (C) 2014 Elsevier B.V. All rights reserved.
Keywords:
Subgroups
Non-redundancy
Odds ratio
Rules
Search space pruning
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K
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7.6
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1.2W
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4.5W
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