An interpretable machine learning model for predicting cavity water depth and cavity length based on XGBoost–SHAP

An interpretable machine learning model for predicting cavity water depth and cavity length based on XGBoost–SHAP

In contrast to the traditional black box machine learning model, the white box model can achieve higher prediction accuracy and accurately evaluate and explain the prediction results. Cavity water depth and cavity length of aeration facilities are predicted in this research based on Extreme Gradient...

Full description

Bibliographic Details
Main Authors: Tiexiang Mo, Shanshan Li, Guodong Li
Format: Article
Language:English
Published: IWA Publishing 2023-07-01
Series:Journal of Hydroinformatics
Subjects:
bayesian optimization
cavity length
cavity water depth
shap
white box model
xgboost
Online Access:http://jhydro.iwaponline.com/content/25/4/1488

Internet

http://jhydro.iwaponline.com/content/25/4/1488

Similar Items