Finding Perfect-Predictor Feature Sets for Supervised Classification Using Genetic Algorithms
نویسنده
چکیده
In some supervised classification problems, the presence of a particular subset of features may be perfectly predictive of a data point’s class label. Discovery of these perfect-predictor feature sets can be used to explore the data and help create new features that capture dependencies among existing features. In this paper, we test the capability of genetic algorithms for finding perfect-predictor feature sets and describe limitations.
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تاریخ انتشار 2011