model-selection-guide
ML model selection matrix by problem type, hyperparameter tuning strategies, and ensemble methodology guide. Use this skill for ML model selection and design involving 'model selection', 'algorithm comparison', 'hyperparameter tuning', 'Optuna', 'ensemble', 'XGBoost vs LightGBM', 'model comparison', 'cross-validation', etc. Enhances the model-designer and evaluation-analyst's model design capabilities. Note: data preprocessing and training infrastructure management are outside this skill's scope.
Installation and usage
ML model selection matrix by problem type, hyperparameter tuning strategies, and ensemble methodology guide. Use this skill for ML model selection and design involving 'model selection', 'algorithm comparison', 'hyperparameter tuning', 'Optuna', 'ensemble', 'XGBoost vs LightGBM', 'model comparison', 'cross-validation', etc. Enhances the model-designer and evaluation-analyst's model design capabilities. Note: data preprocessing and training infrastructure management are outside this skill's scope.
Après l'installation, vous pouvez utiliser ce skill en exécutant la commande suivante dans votre terminal :
skills use model-selection-guide