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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 is one of the most efficient data mining techniques in Machine Learning. In classification, Decision trees can handle high dimensional data. But, decision trees yield poor performance in medical health care. So, In this paper, we investigate the use of Receiver Operating Characteristic (ROC) curve for the evaluation of machine learning algorithms. In particular, we investigate the use...
Traditional chinese medicine (TCM) is one of the most important complementary and alternative medicines. In this paper, a novel computerized diagnostic method based on decision tree (DT) is proposed for promoting standardization and popularization of TCM diagnosis. In TCM, the symptoms are often high dimensional. Although DT induction algorithm has a feature selection scheme included in its learning...
The use of data mining approaches in the domain of medicine is increasing rapidly. The effectiveness of these approaches to classification and prediction has improved the performance of their systems. These are particularly useful to medical practitioners in decision making. In this paper, we present an analysis of prediction of the survivability of the burn patients. The machine learning algorithm...
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