I. B. Yashkov

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A method of feature selection is considered for training a classification algorithm based on the JSM method. The method is based on the use of decision trees. It includes construction of a maximal tree using the C4.5 algorithm and the preparation of a series of truncated trees based on the criterion of minimal cost complexity. The results and parameters of(More)
Preprocessing methods for handling problems with features containing continuous attributes are discussed for learning a classification algorithm based on the JSM method. Discretization methods for continuous parameters that do not make use of class information on feature distribution are compared to entropy-based methods employing class labels in interval(More)
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