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Time Series Shapelets
A pool of time series, of different length
They are from class A and B, labeled
Find a series of shapelets to optimally split the set
Supervised learning (explicit labeling), training / testing
Decision tree (find an optimal shapelet at each node)
Euclidean distance (basically distance measure only computed for subsequences with the same length)
Some modification applied to brute force method to reduce complexity and storage
Brute force algorithm:
1. Early abandon (faster)
2. Admissible entropy pruning (faster)
Classification by decision tree:
Impurity measures: entropy, Gini, classification error
Comments for our problem:
We don’t need to find an optimal shapelet: our reference subsequence is already quite short
We can break down the long time series into small pieces, and regard it as a pool, but we do not have explicit labels, it is not a supervised learning problem.
Source: Ye, L. & Keogh, E. Data Min Knowl Disc (2011) 22: 149. https://doi.org/10.1007/s10618-010-0179-5
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