A New Ensemble Approach to Predict Breast Cancer Manikandan G.1,*, Poigai J.2, Krishnan R. Bala3, Karthikeyan B.4, Rajendiran P.5 1Senior Assistant Professor, School of Computing, SASTRA Deemed University, Thanjavur, India 2Student, School of Computing, SASTRA Deemed University, Thanjavur, India 3Assistant Professor, Srinivasa Ramanujan Centre, SASTRA Deemed University, Thanjavur, India 4Senior Assistant Professor, School of Computing, SASTRA Deemed University, Thanjavur, India 5Assistant Professor, School of Computing, SASTRA Deemed University, Thanjavur, India *Corresponding Author: G. Manikandan, Senior Assistant Professor, School of Computing, SASTRA Deemed University, Thanjavur, India, e-mail: manikandan@it.sastra.edu
Online published on 23 December, 2019. Abstract The primary objective of using a variety of Data mining techniques in health care domain is to construct a useful model that can effectively interpret the data from a cluster of medical datasets. To reveal the hidden pattern in data, Data Mining techniques and algorithms rely on a wide variety of machine learning techniques. Classification along with prediction techniques play an essential role in medical decision making. This type of knowledge-based system can aid doctors in predicting the disease accurately. The main objective of this paper is to create an ensemble of classification algorithms to classify the cancer data set with higher classification accuracy when compared with the existing classification algorithms available in the literature. Top Keywords Data mining, Classification, Ensemble Learning, Bagging, Boosting. Top |