Identification of online auction bidding robots using machine learning

Abstract

The aim of this project is to identify the bidding robots using machine learning, which bids in an online auction. Bidding robot is basically an application which helps to place a bid or click automatically on a website. So, this project will help the site owners to prevent unfair auction by easily flag the robots and remove them from their sites. The major steps are feature extraction, feature selection, model implementation, and classification. Feature engineering is done which includes feature extraction, dropping unnecessary features, and selecting necessary features. Various machine learning classification models are applied with new features to classify human and robot online auction bids and the best performance achieved is ROC score 0.954 using Random Forest.