Model Tuner Documentation
- iPython Notebooks
- Key Methods and Functionalities
- Helper Functions
- Input Parameters
- Caveats
- Model Calibration
- Binary Classification
- AIDS Clinical Trials Group Study
- Step 1: Import Necessary Libraries
- Step 2: Load the dataset, define X, y
- Step 3: Check for zero-variance columns and drop accordingly
- Step 4: Create an Instance of the XGBClassifier
- Step 5: Define Hyperparameters for XGBoost
- Step 6: Initialize and Configure the
Model
- Step 7: Perform Grid Search Parameter Tuning
- Step 8: Fit the Model
- Step 9: Return Metrics (Optional)
- Step 10: Calibrate the Model (if needed)
- Classification Report (Optional)
- AIDS Clinical Trials Group Study
- Regression