| """Train an Iris flower classifier and save it as model.joblib.""" | |
| import joblib | |
| from sklearn.datasets import load_iris | |
| from sklearn.ensemble import RandomForestClassifier | |
| from sklearn.metrics import accuracy_score | |
| from sklearn.model_selection import train_test_split | |
| data = load_iris() | |
| X_train, X_test, y_train, y_test = train_test_split( | |
| data.data, data.target, test_size=0.2, random_state=42, stratify=data.target | |
| ) | |
| model = RandomForestClassifier(n_estimators=100, random_state=42) | |
| model.fit(X_train, y_train) | |
| acc = accuracy_score(y_test, model.predict(X_test)) | |
| print(f"Test accuracy: {acc:.2%}") | |
| joblib.dump({"model": model, "classes": list(data.target_names)}, "model.joblib") | |
| print("Saved model.joblib") | |