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Found 3 papers, 3 papers with code
Elastic Similarity and Distance Measures for Multivariate Time Series
Elastic similarity and distance measures are a class of similarity measures that can compensate for misalignments in the time axis of time series data.
TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification
We demonstrate that TS-CHIEF can be trained on 130k time series in 2 days, a data quantity that is beyond the reach of any TSC algorithm with comparable accuracy.
Proximity Forest: An effective and scalable distance-based classifier for time series
We demonstrate on a 1M time series Earth observation dataset that Proximity Forest retains this accuracy on datasets that are many orders of magnitude greater than those in the UCR repository, while learning its models at least 100, 000 times faster than current state of the art models Elastic Ensemble and COTE.
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