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Performance Analysis of Classification Algorithms for Breast Cancer Diagnosis

E. Swathipriya, N. Subha, B. Gomathy

Abstract


In recent times, Breast cancer has become one of the common disease among women. Few of the important root causes for breast cancer is urbanization and adoption of modernized culture. Most of the cancer cases are diagnosed only during the last phase of the disease and thus early detection of the disease has become a crucial task. This paper analysis the performance of four classification algorithms on a breast cancer dataset and speculates the ideal one. Based on the accuracy, appropriate algorithm is chosen and the useful information thus obtained as an outcome is used for breast cancer Diagnosis. During the prediction process Rapid miner 6.0 tool is used to apply data mining algorithms on the cancer dataset.

Keywords


Classifier, Decision Tree, Entropy, Information Gain, Linear Regression, Pruning, Support Vector Machine.

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