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In the covering information system with decision-making (CISD), τ-lower and upper approximation operators are introduced, and some corresponding properties are discussed. This paper also explores reductions of a covering which is based on a new concept of the degree of approximate dependency, and proposes a reduction algorithm based on the importance degree. After reduction, a decision tree is generated...
Classification algorithm is a kind of important technology in data mining, and the most commonly used is decision tree learning. In the process of constructing a decision tree, the selecting criteria of splitting attributes will directly affect the classification results. And the attribute selection of the traditional decision tree algorithm is based on information theory. In this paper, by combining...
This paper presents a new approach for constructing decision trees based on variable precision rough set model. The presented approach is aimed at handling uncertain information during the process of inducing decision trees and generalizes the rough set based approach to decision tree construction by allowing some extent misclassification when classifying objects. In the paper, variable precision...
The attribute reduction of information system can improve the accuracy of knowledge discovery, machine learning, etc. and it also can improve the efficiency. This paper proposes an attribute testing reduction algorithm, the algorithm can make the information system retain as few as attributes under the condition that maintains the original style, it can not only save much time for the later system...
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