README.md

metadata

license: cc-by-4.0
task_categories:
  - time-series-forecasting
tags:
  - time-series
  - forecasting
  - anomaly-detection
  - classification
  - TSLib
  - tsfile
  - modality:timeseries
  - timeseries
  - format:tsfile
pretty_name: UWaveGestureLibrary (TsFile)
size_categories:
  - 1M<n<10M
configs:
  - config_name: default
    data_files:
      - split: train
        path: UWaveGestureLibrary_train.tsfile
      - split: test
        path: UWaveGestureLibrary_test.tsfile
modality:
  - timeseries
  - tabular
  - text
language:
  - en

UWaveGestureLibrary (TsFile)

Apache TsFile version of the UWaveGestureLibrary UEA classification subset of thuml/Time-Series-Library.

Overview

Accelerometer traces of eight hand gestures; classify the gesture.

• Train samples: 120 • Test samples: 320.
• Dimensions (channels): 3 • Series length: 315.
• Classes: 8.

Each sample is an independent multivariate series. TRAIN and TEST are stored as two separate TsFiles (UWaveGestureLibrary_train.tsfile / UWaveGestureLibrary_test.tsfile).

Schema (TsFile structure)

• sample_index (TAG) — one device per sample. Query one sample with WHERE sample_index=0.
• Time (INT64) — within-sample position (0..314); a frame index, not a wall-clock timestamp (the sktime .ts source has none).
• dim_0 … dim_2 (FIELD, FLOAT) — the 3 channels at each position.
• class_label (FIELD, STRING) — the sample's class, repeated on every row.

Converted from the sktime .ts format. Nothing is dropped: every dimension, time point, and label is preserved.

Usage

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

Source & license

• Original dataset: https://huggingface.co/datasets/thuml/Time-Series-Library (subset UWaveGestureLibrary)
• Author / publisher: thuml (Tsinghua University)
• Paper: https://arxiv.org/abs/2407.13278
• License: CC BY 4.0