Analysis of Different Machine Learning Algorithms Used for Identification of Lung Cancer Disease

Cancer is a curable disease if its diagnosis is done in earlier stages. Study has concluded that the mortality rate is decreasing because of increasing in cancer disease. There are several types of cancer and in the recent survey of India and worldwide lung cancer was found to be second most dangerous disease that causes maximum deaths. Various studies were conducted in detecting cancer at earlier stages using Machine learning and Artificial intelligence so that we can cure the patients and save their lives to some extent. Various methods have been invented and applied by a combination of biomedical image processing method and knowledge Detection of Data. In this research work we have applied some machine learning algorithms on lung cancer disease dataset and have calculated accuracy, sensitivity, specificity, F1 score and Precision. The key idea of our research work is analysis of initial stage lung cancer by inspecting the performance of various machine learning algorithms. Here in our research work we have considered the Multinomial Nave Bayes, Logistic regression, Random forest, Ridge Classifier and SGD classifier on lung cancer data set.