1 code implementation • 31 Oct 2023 • Arik Ermshaus, Patrick Schäfer, Ulf Leser
Ubiquitous sensors today emit high frequency streams of numerical measurements that reflect properties of human, animal, industrial, commercial, and natural processes.
1 code implementation • Advanced Analytics and Learning on Temporal Data 2023 • Arik Ermshaus, Patrick Schäfer, Anthony Bagnall, Thomas Guyet, Georgiana Ifrim, Vincent Lemaire, Ulf Leser, Colin Leverger, Simon Malinowski
Despite its importance, existing methods demonstrate limited efficacy on real-world multivariate time series data.
3 code implementations • 25 Apr 2023 • Matthew Middlehurst, Patrick Schäfer, Anthony Bagnall
We introduce 30 classification datasets either recently donated to the archive or reformatted to the TSC format, and use these to further evaluate the best performing algorithm from each category.
2 code implementations • Advanced Analytics and Learning on Temporal Data 2023 • Arik Ermshaus, Patrick Schäfer, Ulf Leser
We provide, for the first time, a systematic survey and experimental study of 6 TS window size selection (WSS) algorithms on three diverse TSDM tasks, namely anomaly detection, segmentation and motif discovery, using state-of-the art TSDM algorithms and benchmarks.
1 code implementation • 24 Jan 2023 • Patrick Schäfer, Ulf Leser
Time series classification (TSC) is the task of assigning a time series to one of a set of predefined classes, usually based on a model learned from examples.
2 code implementations • 28 Jul 2022 • Arik Ermshaus, Patrick Schäfer, Ulf Leser
Such processes often consist of multiple states, e. g. operating modes of a machine, such that state changes in the observed processes result in changes in the distribution of shape of the measured values.
Ranked #1 on Change Point Detection on TSSB (Covering metric)
1 code implementation • 8 Jun 2022 • Patrick Schäfer, Ulf Leser
Motif discovery (MD) is the task of finding such motifs in a given input series.
2 code implementations • International Conference on Information & Knowledge Management 2021 • Patrick Schäfer, Arik Ermshaus, Ulf Leser
In our experimental evaluation using a benchmark of 98 datasets, we show that ClaSP outperforms the state-of-the-art in terms of accuracy and is also faster than the second best method.
Ranked #1 on Change Point Detection on TSSB
1 code implementation • 15 Jul 2020 • Felix Mujkanovic, Vanja Doskoč, Martin Schirneck, Patrick Schäfer, Tobias Friedrich
Modern time series classifiers display impressive predictive capabilities, yet their decision-making processes mostly remain black boxes to the user.
1 code implementation • 30 Nov 2017 • Patrick Schäfer, Ulf Leser
Multivariate time series (MTS) arise when multiple interconnected sensors record data over time.
1 code implementation • 26 Jan 2017 • Patrick Schäfer, Ulf Leser
On the popular UCR benchmark of 85 TS datasets, WEASEL is more accurate than the best current non-ensemble algorithms at orders-of-magnitude lower classification and training times, and it is almost as accurate as ensemble classifiers, whose computational complexity makes them inapplicable even for mid-size datasets.