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Dynamic time warping (DTW) measures similarity between two data sequences by minimizing an accumulated distance between two sequence samples at each iteration and a cost is computed to assess the level of the similarity. The DTW cost may then be used to assign a sequence to a class if the problem is a classification problem. In machine learning, classification problems are solved using features with...