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A Critical Study of Significant Classification Techniques for Diagnosis of Breast Cancer

Kiran Kumar Reddi, Raja Rajeswari Pothuraju, Sambasiva Rao Voleti


Breast cancer is one of the leading cancers for women in developed countries including India. The classification of breast cancer patients is one of the challenging research problems. This paper comes with the selected classification algorithms for the classification of breast cancer patient datasets. The implementation is done using the application of Bayes Net, Naïve Bayes classifier, C4.5, Back propagation, and Support Vector Machines. The performance of the algorithm is evaluated using classification accuracy, sensitivity, specificity, and precision values. The experiments are done using 10 fold cross validation method. The results obtained by Bayes Net are superior by other classifiers


Data Mining, Classification Algorithms, Breast Cancer Diagnosis.

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