Fast Feature Selection by Analyzing Class Regions Approximated by Ellipsoids
نویسندگان
چکیده
In our previous work, we have developed the backward feature selection method based on class regions approximated by ellipsoids. In this paper, we accelerate feature selection by the forward selection search, the symmetric Cholesky factorization, and deletion of duplicated calculations between consecutive factorizations. The feature selection for two data sets shows that our method is faster than and as robust as the previous method.
منابع مشابه
Feature selection by analyzing class regions approximated by ellipsoids
In our previous work, we have developed a method for selecting features based on the analysis of class regions approximated by hyperboxes. In this paper, we select features analyzing class regions approximated by ellipsoids. First, for a given set of features, each class region is approximated by an ellipsoid with the center and the covariance matrix calculated by the data belonging to the clas...
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