A Comparison of different learning models used in Data Mining for Medical Data
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The present study aims at investigating the different Data mining learning models for different medical data sets and to give practical guidelines to select the most appropriate algorithm for a specific medical data set. In practical situations, it is absolutely necessary to take decisions with regard to the appropriate models and parameters for diagnosis and prediction problems. Learning models and algorithms are widely implemented for rule extraction and the prediction of system behavior. In this paper, some of the well‐known Machine Learning(ML) systems are investigated for different methods and are tested on five medical data sets. The practical criteria for evaluating different learning models are presented and the potential benefits of the proposed methodology for diagnosis and learning are suggested.