Applying CST on Medical Datasets
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classification accuracy, case slicing technique, decision making, slicing.
Abstract
An important component of many data mining projects is finding a good classification algorithm; Case Slicing Technique (CST) is a classification algorithm based on program slicing techniques is examined in solving the classification problems in medical domain. The technique is experimented with three medical datasets, Hepatitis Domain (HEPA), Heart Disease (CLEV) and Breast Cancer (BCO) datasets. The experimental results are compared with other classification algorithms, K-Nearest Neighbor (K-NN) and Naïve Bayes (NB). The experimental result shows that the slicing technique is a promising classification algorithm in solving the decision making in medical classification problem.
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