28 A Hybrid Improving Schema between ID3 Algorithms and Naive Bayes Classifiers and Its Application to the Population Database of Breast Cancer
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Analyzed the principles of the ID3 algorithm, this creates rules based on the concepts of entropy and gain with prepared data set. On the other hand, na1ve Bayes classifier, allow us to classify through of the prepared data set considered probabilistic evidence. We propose a hybrid schema based on the ID3 algorithm and the na1ve Bayes classifier that let us to improve the accuracy in classification tasks. We believe that this may be useful in many types of applications, so this schema serve as a support tool for research as a way to make decisions. Finally, we use experiment to prove that the hybrid schema increase the accuracy being applied to population databases of breast cancer.