Abstract:

The classification of genetic ranges plays an important role in the prevention or diagnosis of diseases. It is important that the genes (properties) containing the necessary information to be able to make an effective classification on the entire genes are not possible because it is important that the genes (properties) contain the necessary information to be able to make a healthy classification with character reduction algorithms. In this study, intuitive search techniques to reduce characteristics, character reduction approaches(filter, wrapper, etc.) Analysis of different methods such as the more efficient implementation of the pre-processing step; the resulting data sets are more efficiently classified by powerful classification tools such as LR (Logistic Regression) and SVM (Support Vector Machines). The LR classifier, which is considered a strong classifier in machine learning, has become a valid and effective classification tool as SVM in the classification of characteristic distribution methods and genetic ranges.

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