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