Train prediction models on tables and CSVs.
What it does
Guides implementation and tuning of XGBoost and LightGBM models for classification and regression on tabular data.
When to use it
Use for tabular classification or regression, feature selection, imbalanced datasets, and hyperparameter tuning with cross-validation.
How to use it
It changes how the agent implements tabular machine learning, emphasizing early stopping, validation monitoring, and feature-importance checks.
What you provide
- An existing project
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What you need · 2
The guide covers model implementation using the xgboost library.
The guide covers model implementation using the lightgbm library.
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