Enhanced Lung Cancer Prediction Using Ensemble Machine Learning Algorithms

Lung cancer is one among critical diseases and numerous people are suffering from this disease. Lung cancer is not only caused by smoking cigarettes, pipes or cigars; other risk factors include exposure to second-hand smoke (passive smoking), air pollution, radon, familial history of lung cancer and asbestos as a pollutant in the atmosphere. Predicting lung cancer in an earlier stage can help more lung cancer survivors live longer. The classification and prediction accuracy are not so high in the existing methods. In this work, the proposed Lung Cancer prediction model uses Machine learning algorithms with a lung cancer dataset of sixteen attributes for better classification of lung cancer which includes few etiological factors responsible for lung cancer along with regular factors such as Smoking, Yellow Fingers, Anxiety, Peer Pressure, Chronic diseases, etc., Classification accuracy is boosted with Ensemble techniques like Bagging, Boosting and Voting