OnlineNewsPopularity Project
As a part of Automated Learning and Data Analysis in R, I have implemented supervised machine learning techiques (SVM, KNN, SVM, Logistic regression, Naive Bayes, Random Forests, Decision Tree and Gradient Boosting) to predict the popularity of the news article using the dataset from UCI's Machine Learning repository. Using F1 and AUC measure, we have tried to estimate the most important features in the dataset. We have also tried to suggest changes in the news article to make it popular using the best classifier(GBM and SVM).