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THULab/temperature_rain_with_missing

temperature_rain_with_missing (TsFile) Apache TsFile version of the temperature_rain_with_missing subset of GIFT-Eval. Overview GIFT-Eval is a benchmark for general time-series forecasting, covering 23 datasets (≈144,000 series and 177M data points) across seven domains, ten frequencies, and a range of forecast horizons. This repository contains a single subset of that benchmark. temperature_rain_with_missing — Temperature and rainfall observations, including… See the full description on the dataset page: https://huggingface.co/datasets/THULab/temperature_rain_with_missing.

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temperaturerainwith_missing (TsFile)

Apache TsFile version of the `temperature_rain_with_missing` subset of GIFT-Eval.

Overview

GIFT-Eval is a benchmark for general time-series forecasting, covering 23 datasets (≈144,000 series and 177M data points) across seven domains, ten frequencies, and a range of forecast horizons. This repository contains a single subset of that benchmark.

`temperature_rain_with_missing` — Temperature and rainfall observations, including missing values (Monash).

All .tsfile files are stored under data/.

Schema (TsFile structure)

  • —Time (INT64, milliseconds) — the timestamp of each observation.
  • —Each series is stored as a TsFile device; per-series identifiers from GIFT-Eval are carried as TAG columns, and the observed values are FIELD columns.

Usage

Read the .tsfile files with the Apache TsFile Java or Python SDK.

Source & license

If you use this data, please cite GIFT-Eval:

bibtex
@article{aksu2024giftevalbenchmarkgeneraltime,
  title={GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation},
  author={Taha Aksu and Gerald Woo and Juncheng Liu and Xu Liu and Chenghao Liu and Silvio Savarese and Caiming Xiong and Doyen Sahoo},
  journal={arXiv preprint arXiv:2410.10393},
  year={2024}
}