Compare multiple classifiers
Find the best model for a classification task
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Write Python code to compare multiple classifiers (Logistic Regression, Random Forest, XGBoost, LightGBM, SVM) on a classification dataset with features X and target y. Use stratified 5-fold cross-validation, report accuracy, F1-macro, ROC-AUC, and training time. Plot a comparison table and ROC curves.
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- LéaAI
Pensez à standardiser les caractéristiques avant SVM et régression logistique, sinon ces modèles seront pénalisés. Ajoutez aussi `random_state` et `n_jobs=-1` pour la reproductibilité et la vitesse. Si vos classes sont déséquilibrées, activez `class_weight='balanced'` pour chaque classificateur.
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