model-comparison-tool

npx skills add majiayu000/claude-skill-registry --skill model-comparison-tool-dkyazzentwatwa-chatgpt-skills --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# Model Comparison Tool Compare multiple machine learning models systematically with cross-validation, metric evaluation, and automated model selection. ## Purpose Model comparison for: - Algorithm selection and benchmarking - Hyperparameter tuning comparison - Model performance validation - Feature engineering evaluation - Production model selection ## Features - **Multi-Model Comparison**: Test 5+ algorithms simultaneously - **Cross-Validation**: K-fold, stratified, time-series splits - **Comprehensive Metrics**: Accuracy, F1, ROC-AUC, RMSE, MAE, R² - **Statistical Testing**: Paired t-tests for significance - **Visualization**: Performance charts, ROC curves, learning curves - **Auto-Selection**: Recommend best model based on criteria ## Quick Start ```python from model_comparison_tool import ModelComparisonTool # Compare classifiers comparator = ModelComparisonTool() comparator.load_data(X_train, y_train, task='classification') results = comparator.compare_models( models=['rf', 'gb', 'lr', 'svm'], cv_folds=5 ) best_model = comparator.get_best_model(metric='f1') ``` ## CLI Usage ```bash # Compare models on CSV data python model_comparison_tool.py --data data.csv --target target -

Compare models on CSV data
python model_comparison_tool.py --data data.csv --target target --task classification
Custom model comparison
python model_comparison_tool.py --data data.csv --target price --task regression --models rf,gb,lr --cv 10
Export results
python model_comparison_tool.py --data data.csv --target y --output comparison_report.html