Prediction of Lung Cancer Using Machine Learning Techniques and their Comparative Analysis

Description

The project attempts to evaluate the discriminative power of several predictors in the study to increase the efficiency of lung cancer detection through their symptoms. A number of classifiers including Support Vector Machine (SVM), Logistic Regression, Decision Tree, k- Nearest Neighbour and Naïve Bayes (NB) are evaluated on a benchmark dataset obtained from Kaggle repository.