Ensemble Classification Algorithms for Breast Cancer Prognosis
Nitasha1, Rajeev Kumar Bedi2, SK Gupta3

1Nitasha*, Pursuing M.tech CSE from Beant College of Engineering and Technology, PTU, Punjab.
2Rajeev Kumar Bedi Associate Professor of CSE Dept in BCET, Gurdaspur Punjab.
3Dr.SK Gupta Professor of CSE Dept. in BCET Gurdaspur.

Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 1499-1502 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6886129219/2019©BEIESP | DOI: 10.35940/ijitee.B6886.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Breast Cancer is the second highest reason for the death rate among women as well as men too in world. In this paper, we used Data mining classification algorithms to find the presence of breast cancer whether it is benign or malignant and analysis is done on the basics of accuracy and time taken in build model. The data is collected from WISCONSIN of UCI machine learning Repository, which includes patient’s samples. The dataset undergoes different algorithm with and without feature selection. 
Keywords: Ensemble Classification Algorithms, Feature Selection Techniques, Vote Naive Bayes & J48, Random Forest
Scope of the Article: Classification