Predicting online user behaviour using deep learning algorithms

Understand

We propose a robust classifier to predict buying intentions based on user behaviour within a large e-commerce website.

• In this work we compare traditional machine learning techniques with the most advanced deep learning approaches.
• We show that both Deep Belief Networks and Stacked Denoising auto-Encoders achieved a substantial improvement by extracting features from high dimensional data during the pre-train phase.
• They prove also to be more convenient to deal with severe class imbalance.