eng Oriental Scientific Publishing Company Biosciences Biotechnology Research Asia 0973-1245 2017-03-25 14 1 409 414 10.13005/bbra/2459 21840 article Tamilvanan 1 V. Murali Bhaskaran 2 Research and Development Centre, Bharathiar University, Coimbatore-641046, Tamil Nadu, India. Dhirajlal Gandhi College of Technology, Salem-636290, Tamil Nadu, India. 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. https://www.biotech-asia.org/vol14no1/a-new-feature-selection-techniques-using-genetics-search-and-random-search-approaches-for-breast-cancer/ Correlation-based Feature Selection; Data Mining; Genetic Algorithm; Random Search and Naive Bayes Algorithm