Guide-linked quiz · Medium Level
Dynamic Time Warping Quiz
Trace DTW's cumulative alignment path and understand how warping constraints, local costs and normalization affect sequence comparisons.
Question 1 of 8
What variation is DTW designed to accommodate when comparing sequences?
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Answers and explanations appear as you take the quiz.
- What variation is DTW designed to accommodate when comparing sequences?
- Different timing or execution speed
- Different class-label names
- Arbitrary changes in feature meaning
- Missing all observations
- What does the dynamic-programming cost matrix accumulate?
- The average value of both sequences
- The lowest allowed path cost up to each pair of positions
- The number of labels per sequence
- A probability that the alignment is causal
- Why constrain the warping path near the diagonal?
- To make all distances satisfy triangle inequality
- To force every pair to match exactly at the same index
- To prevent implausible extreme timing matches
- To remove local costs from the calculation
- What can unrestricted warping do to unrelated sequences?
- Preserve sampling rates automatically
- Guarantee a semantic match
- Make every local cost zero
- Align distant or mismatched events through excessive stretching
- Which quantity commonly defines the cost in one cell of the DTW matrix?
- The product of sequence lengths
- A distance between feature vectors at two time positions
- The cluster count
- The global mean of each series only
- Why should normalization be consistent across sequences?
- A DTW path has no cumulative cost
- Normalization forces all alignments to be identical
- Path-length normalization changes the scale of reported distances
- The method becomes a classifier automatically
- Which property is not guaranteed for standard DTW distance?
- Matching both endpoints
- A monotone alignment path
- A cumulative local cost
- Triangle inequality
- What should a reviewer inspect alongside a DTW score?
- The alignment path and whether its timing distortions are plausible
- Only the sequence length
- The alphabetical order of frames
- The number of clusters in an unrelated model
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