Question

Provide a code snippet to perform K-Nearest Neighbors (KNN) with 5 neighborhoods and subsequently evaluate the model fit.

Answer 1

This Python code snippet utilizes the scikit-learn library to implement K-Nearest Neighbors (KNN) with 5 neighbors. It includes creating a KNN classifier, training the model with training data, making predictions on test data, and evaluating model accuracy using the accuracy_score metric from scikit-learn.

Step-by-step explanation:

This Python code snippet employs the scikit-learn library for implementing K-Nearest Neighbors (KNN) with 5 neighbors.

It involves creating a KNN classifier, training the model with designated training data (X_train, y_train), and generating predictions for test data (X_test).

The subsequent section illustrates the evaluation of model fit, showcasing the use of various performance metrics such as accuracy.

The accuracy_score metric from scikit-learn is employed to calculate accuracy, offering insights into the model's predictive capability.

This comprehensive approach to KNN implementation and model evaluation enhances clarity and usability, making it a valuable resource for machine learning practitioners seeking effective classification techniques.