Predict Future Sales using Ensembled Random Forests
Machine Learning
2019-04-22 v1
Abstract
This is a method report for the Kaggle data competition 'Predict future sales'. In this paper, we propose a rather simple approach to future sales predicting based on feature engineering, Random Forest Regressor and ensemble learning. Its performance turned out to exceed many of the conventional methods and get final score 0.88186, representing root mean squared error. As of this writing, our model ranked 5th on the leaderboard. (till 8.5.2018)
Keywords
Cite
@article{arxiv.1904.09031,
title = {Predict Future Sales using Ensembled Random Forests},
author = {Yuwei Zhang and Xin Wu and Chenyang Gu and Yueqi Xie},
journal= {arXiv preprint arXiv:1904.09031},
year = {2019}
}