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What is k-Nearest Neighbor Algorithm Explained about?

Lecture 8 covers the k-Nearest Neighbor (kNN) algorithm, which classifies data based on the principle that similar instances share similar labels. It discusses the strengths and weaknesses of kNN, the importance of choosing the right value for k, and the need for data normalization to ensure accurate distance measurements. The lecture also contrasts lazy and eager learning strategies, highlighting that kNN is a lazy learner that stores training data for classification.

Author

Nour Ramadan

Language

EN