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Objectives:The proposed work is to classify breast cancer with few attributes. Reducing the attributes reduces the time, so that the patient need not wait for result for a long time. For

Breast cancer has become a common factor now-a-days. Despite the fact, not all general hospitalshave the facilities to diagnose breast cancer through mammograms. Waiting for diagnosing a breastcancer for a long time may increase the possibility of the cancer spreading. Therefore a computerizedbreast cancer diagnosis has been developed to reduce the time taken to diagnose the breast cancer andreduce the death rate. This paper summarizes the survey on breast cancer diagnosis using various machinelearning algorithms and methods, which are used to improve the accuracy of predicting cancer. This surveycan also help us to know about number of papers that are implemented to diagnose the breast cancer