K-nearest neighbors (KNN) is a simple, yet powerful, algorithm used for classification and regression tasks in machine learning. It works by identifying the 'k' closest data points to a given query point based on a distance metric, usually Euclidean distance, and making predictions based on the majority class or average value of these neighbors. This method is intuitive and effective for exploratory data analysis, helping to uncover patterns and relationships within datasets.
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