There was rapid boom of software program development. Due to numerous reasons, the software program comes with many defects. In latest years, defect prediction, one of the principal software program engineering problems, has been inside the consciousness of researchers because it has a pivotal function in estimating software program errors and defective modules. Researchers with the intention of enhancing prediction accuracy have advanced many models for software program defect prediction. But, there are a number of crucial conditions and theoretical issues a good way to reap higher consequences. In this paper, we are able to be discussing SVM classifier, Naïve bayes classifier ,logistic regression, decision tree and KNN with cross validation is used to locate the accuracy. The effects show that consistency in high accuracy prediction turned into done the use of this strategies.

defect prediction; SVM classifier; Naïve bayes; Logistic Regression ,Decision Tree ,KNN