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In this paper mainly deals with various classification algorithm techniques with feature extraction algorithm used to improve the predicated accuracy of the algorithm. This paper applied with correlation based feature selection as a feature evaluator and Genetics and random searching method. The results of the classification model are sensitive, specificity, precision, time, and accuracy. Finally, it concludes that the proposed CFL-NB algorithm performance is better than other classification algorithms techniques for breast cancer disease.

A New Feature Selection Techniques Using Genetics Search and Random Search Approaches For Breast Cancer