Chi2: Feature Selection and Discretization of Numeric Attributes (1995)
| Venue: | In Proceedings of the Seventh International Conference on Tools with Artificial Intelligence |
| Citations: | 66 - 14 self |
BibTeX
@INPROCEEDINGS{Liu95chi2:feature,
author = {Huan Liu and Rudy Setiono},
title = {Chi2: Feature Selection and Discretization of Numeric Attributes},
booktitle = {In Proceedings of the Seventh International Conference on Tools with Artificial Intelligence},
year = {1995},
pages = {388--391}
}
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Abstract
Discretization can turn numeric attributes into discrete ones. Feature selection can eliminate some irrelevant attributes. This paper describes Chi2, a simple and general algorithm that uses the 2 statistic to discretize numeric attributes repeatedly until some inconsistencies are found in the data, and achieves feature selection via discretization. The empirical results demonstrate that Chi2 is effective in feature selection and discretization of numeric and ordinal attributes. 1 Introduction Feature selection is a task to select the minimum number of attributes needed to represent the data accurately. By using relevant features, classification algorithms can in general improve their predictive accuracy, shorten the learning period, and result in the simpler concepts. There are abundant feature selection algorithms [5]. Our work adopts an approach that selects a subset of the original attributes since it not only has the above virtues, but also serves as an indicator on what kind...
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