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Now a days breast cancer in the world is one of the issuessince this disease occurs second place in the developed country.In medical field providing proper awareness, but the ratio of outreach the people understand the cancer awareness is less. The world health organizationreleased an article that breast cancer is one of the challenging problems and most of women affected by breast cancer sometimes one percentage of possibility for men also. The main aim of the study to analyze breast cancer data based on its characteristics and identify the effectiveness of clustering and classification instructions for analyzing breast cancer data. Breast cancer related images, different characteristics, including numerical data and attributes are used in this research work.Patients intake routine, age, lifestyles, occupation, details of diseases that cause problems are taken and then carry out for machine learning based classification and clustering algorithms.And eventually clustering algorithms like k-Means and Expectation-Maximization (EM), and classification algorithms such as J48, Classification and Regression Trees (CART) and Support Vector Machine (SVM) are trained as well as tested.The overall performance of clustering and classifications are based on sensitivity, specificity, accuracy, error rate and process time.
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