A Study on Prediction Success of Machine Learning Algorithms for Wart Treatment
Kemal Akyol Abdulkadir Karaci Yasemin Gültepe
AbstractData mining and machine learning algorithms are utilized in order to discover meaningful information by thorough analysis of dataset. They are used in multi-disciplinary field. Wart is caused by the human papillomavirus. It inhibits body growth by activating ecdysone steroid production systematically. There are several treatment methods for this illness. These methods focused on offering a solution for people. In this framework, a study on the analysis of the best two wart treatment methods, Cryotherapy and Immunotherapy, is carried out. The first one of these datasets collected by applying the cryotherapy method consists of seven features. The second dataset collected by applying the immunotherapy method consists of eight features. Fuzzy Rule, Naive Bayes and Random Forest based models are designed in order to evaluate the effectiveness of these methods in wart treatment. The performances of these algorithms are judged within the frame of Accuracy and Sensitivity performance measures.