| from sklearn.datasets import load_iris | |
| from sklearn.ensemble import RandomForestClassifier | |
| from sklearn.model_selection import train_test_split | |
| from sklearn.metrics import accuracy_score | |
| import joblib | |
| iris = load_iris() | |
| X = iris.data | |
| y = iris.target | |
| X_train, X_test, y_train, y_test = train_test_split( | |
| X, y, test_size=0.2, random_state=42 | |
| ) | |
| model = RandomForestClassifier(random_state=42) | |
| model.fit(X_train, y_train) | |
| predictions = model.predict(X_test) | |
| accuracy = accuracy_score(y_test, predictions) | |
| print("Model accuracy:", accuracy) | |
| joblib.dump(model, "iris_classifier.joblib") | |
| print("Model saved as iris_classifier.joblib") |