K-nearest neighbors (KNN) is a simple, yet powerful algorithm used in machine learning for classification and regression tasks. It works by identifying the 'k' closest data points in the training dataset to a given test point and making predictions based on the majority class (for classification) or the average value (for regression) of those neighbors. This method is intuitive and effective, particularly for problems where the relationships between data points are complex and not easily captured by linear models.
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