A Comparative Analysis of Lung Cancer Prediction using Machine Learning Algorithms

In today’s world, with the human’s lifestyle has totally changed as compared to its ancestors which causes many types of life taking diseases. One of them is Lung cancer. The growth of cancer diseases is a big issue yet to be resolved in today’s world. The easiest way to control cancer is to predict it at its earlier stage. The aim of this paper is to examine the different algorithms of machine learning to predict the lung’s cancer and check the algorithm which offer best accuracy so that a reliable, efficient, and robust model can be designed for early detection of lung cancer which can save life of million human beings. The algorithms we have implemented in the implementation of this research are Decision Tree, KNN, and Random Forest. The parameters that we are considering for comparing the best model are Accuracy, Precision, Recall and F1 score.