Dynamic Time Warping (DTW) is an algorithm used to measure similarity between two temporal sequences that may vary in speed or timing. It's particularly useful in fields such as speech recognition, data mining, and bioinformatics, where the sequences of data points can be misaligned due to differences in pacing or distortion. ### Key Features of Dynamic Time Warping: 1. **Alignment of Sequences**: DTW aligns two sequences in a way that minimizes the distance between them.
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