KNN

K-Nearest Neighbors (KNN) is a simple, instance-based learning algorithm used for classification and regression tasks. It operates on the principle that similar instances are likely to have similar outcomes.

• Both classification and regression tasks.
• Classification:
• Find the K closest points to a sample point and return the most frequent label
• Regression:
• Find the K closest points to a sample point and return the average of their values

Hyperparameters

• K: The number of nearest neighbors to consider when making predictions. A larger K value can smooth out noise but may also overlook local patterns.
• sample_size: The number of samples to use from the training data when making predictions. A larger sample size can improve accuracy but may increase computation time.