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Analysis of cancer datasets using Classification Algorithms


Parvesh Kumar, Siri Krishan Wasan


Vol. 10  No. 6  pp. 175-182


Cancer detection is one of the important research topics in medical science. In bioinformatics age, gene expression data can be used for the cancer detection. Data mining techniques, such as pattern association, classification and clustering, are now frequently applied in cancer and gene expressions correlation studies. Classification is very important among these techniques of data mining. Here in this paper we studied various classification algorithms like C4.5, CART, Random Forest, LMT, ADT, Na?ve Bayesian and Bayesian logistic Regression over different cancer dataset. Accuracy is the main objective to estimate the performance of these algorithms over cancer datasets.


Data mining, Classification, Decision tree