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Data-Analysis-with-Pandas-and-Python
The coursewok from Udemy
MachineLearning
Machine Learning Tutorial for Beginners
nafis
i running this code in which x train not defined def _train_random_forest(X_train, y_train, X_test, y_test): """ Function that uses random forest classifier to train the model :return: """ # Create a new random forest classifier rf = RandomForestClassifier() # Dictionary of all values we want to test for n_estimators params_rf = {'n_estimators': [110,130,140,150,160,180,200]} # Use gridsearch to test all values for n_estimators rf_gs = GridSearchCV(rf, params_rf, cv=5) # Fit model to training data rf_gs.fit(X_train, y_train) # Save best model rf_best = rf_gs.best_estimator_ # Check best n_estimators value print(rf_gs.best_params_) prediction = rf_best.predict(X_test) print(classification_report(y_test, prediction)) print(confusion_matrix(y_test, prediction)) return rf_best rf_model = _train_random_forest(X_train, y_train, X_test, y_test)