# Machine Learning/Dynamic Time Warping

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https://en.wikipedia.org/wiki/Dynamic_time_warping

sample script:

import numpy as np import mlpy # Example sequences sequence1 = np.array([1, 3, 4, 9, 8, 2, 1]) sequence2 = np.array([1, 2, 4, 7, 8, 2, 1]) sequence3 = np.array([1, 2, 4, 7, 8, 2, 5]) # Compute DTW distances between sequences dist12, cost12, path12 = mlpy.dtw_std(sequence1, sequence2, dist_only=False) dist13, cost13, path13 = mlpy.dtw_std(sequence1, sequence3, dist_only=False) print("DTW distance between sequence1 and sequence2:", dist12) print("DTW distance between sequence1 and sequence3:", dist13) # Predict which sequence is closer based on DTW distance if dist12 < dist13: print("Sequence 2 is predicted to be closer to sequence 1.") else: print("Sequence 3 is predicted to be closer to sequence 1.")