Wart is a benign tumor that grows on all parts of human body. This paper presents a comparison of performance of various Ensemble classifiers for choosing appropriate method among Cryotherapy and Immunotherapy treatment for treating the Warts. This research work focuses on the Bagging, Boosting and Subspace Ensemble Classifiers for identifying wart treatment. In the current research work, the experimentation has been carried out on the datasets acquired from UCI dataset. From the experimentation results, it was observed that Bagged Trees Ensemble classifier provides a highest classification accuracy of 94.4 % for identifying wart treatment methods. The result also depicted that the Bagged Trees Ensemble classifier outperformed on both Cryotherapy and Immunotherapy datasets. The current work is useful for doctors to pick the best technique for treating the wart and to reduce the overall cost incurred in treatment of warts.
Volume 12 | 07-Special Issue
Pages: 539-544
DOI: 10.5373/JARDCS/V12SP7/20202137