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K-Nearest Neighbors: A Lazy Learner Overview by Shisir Ahmed is a document available to read on EtoBox.

What is K-Nearest Neighbors: A Lazy Learner Overview about?

K-nearest neighbors (KNN) is a lazy learning algorithm that classifies data based on similarity to its nearest neighbors. It is a non-parametric method used for classification where the prediction for a test data point is based on its k nearest neighbors from the training data. The algorithm requires a feature space of training data, a distance metric to calculate distances between data points, and a value for k, the number of nearest neighbors. To classify an unknown data point, its distance is calculated

Author

Shisir Ahmed

Language

EN