k-nearest neighbors (k-NN) is a simple, yet effective, machine learning algorithm used for classification and regression tasks based on the proximity of data points in a feature space. By determining the 'k' closest data points to a given instance, the algorithm makes predictions based on the majority class (in classification) or the average value (in regression) of those neighbors. This method is particularly valuable in structural health monitoring, where it can help in identifying patterns and detecting anomalies within complex data sets.
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