milk volume prediction

Avatar of 洪堯煬.
Avatar of 洪堯煬.

milk volume prediction

M.S. student
Hsinchu, Hsinchu City, Taiwan
In this project, we use a XGBoost and Res-regression model to try to handle the milk volume prediction problem, predict milk volume by datasets include cattle information, which is raised by the Taiwan Provincial Cattle Industry Improvement Association –TPCIIA. Conclusion: 1. Res-regression is better than average and the others traditional model, and get RMSE 5.8.​ 2. XGB regressor well fit this problem because of the data uncompleted and the small amount, finally get RMSE 5.47.

Avatar of the user.
Please login to comment.

Published: 2021 Mar 6th
28
4
0

deep learning
data sciense
python
pytorch
machine learning
XGBoost

Share