I. B. Yashkov

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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)
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)
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