Random Forest Classification Accuracy Calculation

This function uses the Random Forest algorithm to classify the given training set and make predictions on the test set, returning the accuracy of the predictions.

Technology Stack : scikit-learn

Code Type : Machine learning

Code Difficulty : Intermediate

                
                    
def random_forest_classification(X_train, y_train, X_test):
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.metrics import accuracy_score

    # Initialize the Random Forest Classifier
    clf = RandomForestClassifier(n_estimators=100)

    # Train the model
    clf.fit(X_train, y_train)

    # Make predictions
    predictions = clf.predict(X_test)

    # Calculate accuracy
    accuracy = accuracy_score(y_test, predictions)

    return accuracy