K-nearest neighbors (KNN) is a widely used algorithm for supervised learning tasks, such as classification and regression. In supervised learning with KNN, the algorithm learns from a labeled training dataset and makes predictions on unseen data points based on their similarity to the training examples. The Euclidean distance measure is commonly used to quantify the similarity between feature vectors in the input space.
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Putu Fadya (2024). Supervised Learning With KNN Euclidean Distance Methods (https://www.mathworks.com/matlabcentral/fileexchange/130079-supervised-learning-with-knn-euclidean-distance-methods), MATLAB Central File Exchange. 检索来源 .
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