Classification Helper
Train and evaluate classification models with automatic model selection.
Features
- Auto Model Selection: Compare multiple classifiers
- Hyperparameter Tuning: Grid/random search
- Evaluation Metrics: Accuracy, precision, recall, F1, ROC-AUC
- Cross-Validation: K-fold validation
- Confusion Matrix: Detailed error analysis
- Feature Importance: Top predictive features
- Model Export: Save trained models
CLI Usage
python classification_helper.py --data train.csv --target class --test test.csv --output model.pkl
Dependencies
- scikit-learn>=1.3.0
- pandas>=2.0.0
- numpy>=1.24.0
- matplotlib>=3.7.0
- seaborn>=0.12.0