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K-nearest neighbors (KNN) is a simple machine learning algorithm that classifies new data based on similarity. It finds the k closest training examples in the feature space and assigns the new data to the most common class among its neighbors. The algorithm calculates the Euclidean distance between points to determine neighbors. It then assigns the data point to the class with the most votes from its k nearest neighbors.

Author

Anshika Tyagi

Language

EN