Monash University, UEA, UCR Time Series Regression Archive

06/19/2020
by   Chang Wei Tan, et al.
0

Time series research has gathered lots of interests in the last decade, especially for Time Series Classification (TSC) and Time Series Forecasting (TSF). Research in TSC has greatly benefited from the University of California Riverside and University of East Anglia (UCR/UEA) Time Series Archives. On the other hand, the advancement in Time Series Forecasting relies on time series forecasting competitions such as the Makridakis competitions, NN3 and NN5 Neural Network competitions, and a few Kaggle competitions. Each year, thousands of papers proposing new algorithms for TSC and TSF have utilized these benchmarking archives. These algorithms are designed for these specific problems, but may not be useful for tasks such as predicting the heart rate of a person using photoplethysmogram (PPG) and accelerometer data. We refer to this problem as Time Series Regression (TSR), where we are interested in a more general methodology of predicting a single continuous value, from univariate or multivariate time series. This prediction can be from the same time series or not directly related to the predictor time series and does not necessarily need to be a future value or depend heavily on recent values. To the best of our knowledge, research into TSR has received much less attention in the time series research community and there are no models developed for general time series regression problems. Most models are developed for a specific problem. Therefore, we aim to motivate and support the research into TSR by introducing the first TSR benchmarking archive. This archive contains 19 datasets from different domains, with varying number of dimensions, unequal length dimensions, and missing values. In this paper, we introduce the datasets in this archive and did an initial benchmark on existing models.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/31/2018

The UEA multivariate time series classification archive, 2018

In 2002, the UCR time series classification archive was first released w...
research
06/23/2020

Time Series Regression

This paper introduces Time Series Regression (TSR): a little-studied tas...
research
09/12/2019

A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency

sktime is an open source, Python based, sklearn compatible toolkit for t...
research
01/30/2023

Benchmarking optimality of time series classification methods in distinguishing diffusions

Performance benchmarking is a crucial component of time series classific...
research
07/22/2021

A Framework for Imbalanced Time-series Forecasting

Time-series forecasting plays an important role in many domains. Boosted...
research
03/31/2020

Adversarial Attacks on Multivariate Time Series

Classification models for the multivariate time series have gained signi...
research
02/27/2019

Adversarial Attacks on Time Series

Time series classification models have been garnering significant import...

Please sign up or login with your details

Forgot password? Click here to reset