rahulraghatate/Ads-Click-Prediction

To boost the income through ad clicks, it is imperative to understand the significance of the factors affecting ad clicks. After mining through data logs provided by Outbrain,we formulated new learning problem in content ranking based on past clickthrough data to predict which pieces of content (ads) likely to be clicked by global users automatically.We used classification models like Naive Bayes, SVM, Random Forest and Stochastic Gradient Descent algorithms for learning parameterized orderings.

语言：Jupyter Notebook · GitHub 星标：4 · Fork：1

在 GitHub 上查看原仓库