Ensembles of Randomized Time Series Shapelets Provide Improved Accuracy while Reducing Computational Costs

22 Feb 2017Atif RazaStefan Kramer

Shapelets are discriminative time series subsequences that allow generation of interpretable classification models, which provide faster and generally better classification than the nearest neighbor approach. However, the shapelet discovery process requires the evaluation of all possible subsequences of all time series in the training set, making it extremely computation intensive... (read more)

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