Lung Cancer Malignancy detection Using Voting Ensemble Classifier

Lung Cancer is a deadly disease caused by the abnormal and uncontrollable procreation of cells. Cancer can invade other body parts in case of late diagnosis. In this paper, we designed a computer-assisted lung cancer malignancy detection system using the Voting Ensemble classifier. The ensemble was designed by combining Decision Tree, SVM, and KNN as base learners. Each of the base learners was defined five times with different parameters. A total of fifteen weak learners were incorporated while defining the ensemble. The ensemble model attained an accuracy of 97.72%. The Sensitivity, F1-Score, and Precision were obtained as 94.33%, 96.33%, and 98.00% respectively. Our suggested model scored better than other current state-of-the-art approaches.