NEL ensemble learning for CCN prediction

Local Knowledge Graph (32 entities)

Knowledge graph centered on NEL ensemble learning for CCN prediction with 32 nodes and 111 connections. Top connected: leaf water content, spectral reflectance, surface albedo, forecast skill, correlation coefficient.

Description

Novel ensemble learning approach combining XGBoost, CatBoost, and Random Forest algorithms with SHAP interpretability analysis to predict cloud condensation nuclei from aerosol optical properties.

Typical Equipment

• XGBoost
• CatBoost
• Random Forest algorithms
• SHAP algorithm
• Bayesian optimization

Output Measurements

• CCN predictions
• feature importance scores
• model performance metrics

Papers Using This Protocol (1)

Places Where Used