Improving the Performance of Lung Cancer Prediction Using Machine Learning Techniques on Big Data

Abstract

Medical diligences are a main of developing huge amount of data by itself and form a Big Data Lung Cancer is a disease in which cells in the body grow out of control. When cancer starts in the lungs, it is called lung cancer. From this the prediction of lung cancer is so important to save the patient life. Lung cancer data base stores important as well as raw data into database. For predict the important data from database use different Machine Learning techniques to classify the data. This paper classified about various Machine Learning techniques to predict the lung cancer by using dataset. The accuracy, Precision, Recall and F-Measure are calculated for Support Vector Machine, Navi Bayes, K nearest neighbour, Logistic Regression techniques. The result shows the Support Vector Machine algorithm give the best accuracy of 82.25%. Ensemble method of techniques also used to improve accuracy of lung cancer.

Machine Learning Approaches in Early Lung Cancer Prediction: A Comprehensive Review

“…Kasthuri et al used the dataset taken from UCI machine learning repository and implemented in the following machine learning algorithms-SVM, Naïve Bayes, KNN and Logistic Regression. The team predicted an accuracy of 82.25% with SVM model [15].…”