Breast cancer has a reason for the leading cause of death in women in various countries. The popular effective way to decrease breast cancer deaths is to detect it as earlier as possible. The classification of breast cancer data can be useful to predict the outcome of some disease or discover the genetic behavior of tumors. An early diagnosis method requires a more accurate and user reliable diagnosis techniques those are allow physicians to distinguish benign breast tumors from malignant ones without going for surgical biopsy. The objective of this paper is to find the classification of breast cancer as either benign or malignant .Then relative study on different cancer classification approaches viz, KNN, Decision tree and Neural Network classifiers are conducted where the accuracy of each of the classifier is also measured.

Classification techniques; Data mining techniques; breast cancer; Diagnosis; Prognosis

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