OpenTS Overview

OpenTS is a comprehensive and fair benchmarking of time series analytics, mainly including foreacsting and anaomly detection. OpenTS inlucdes a Time series Forecasting Benchmark (TFB) and a Time series Anomaly detection Benchmark (TAB). OpenTS provides comprehensive time series datasets, rich time series analtycis algorithms, and a unified evaluation pipeline with various strategies and metrics.

Comprehensive Datasets

OpenTS offers comprehensive time series benchmark datasets with diverse characteristics from multiple domains and complex settings.

Rich Algorithms

OpenTS covers a diverse range of methods, including statistical learning, machine learning, and deep learning methods.

Unified Pipeline

OpenTS offers a unified pipeline for evaluating time series forecasting and anomaly detection methods under a variety of experiment configuration settings.

Paper (PVLDB 2024 Best Paper Nomination)

Cite Us

@article{qiu2024tfb,
  title   = {TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods},
  author  = {Qiu, Xiangfei and Hu, Jilin and Zhou, Lekui and Wu, Xingjian and Du, Junyang and Zhang, Buang and Guo, Chenjuan and Zhou, Aoying and Jensen, Christian S and Sheng, Zhenli and Bin Yang},
  journal = {Proc. {VLDB} Endow.},
  year    = {2024},
  pages   = {2363 - 2377},
  volume  = {17}
}