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.
@article{arxiv.1511.06247,
title = {Predicting online user behaviour using deep learning algorithms},
author = {Armando Vieira},
journal= {arXiv preprint arXiv:1511.06247},
year = {2016}
}
Comments
21 pages, 3 figures. arXiv admin note: text overlap with arXiv:1412.6601, arXiv:1406.1231, arXiv:1508.03856 by other authors