Datasets › IRIS Multiple Instance Learning Dataset

IRIS Multiple Instance Learning Dataset

Introduced by Cédric Huwyler et al. in Using Multiple Instance Learning for Explainable Solar Flare Prediction25 Mar 2022 archive 2025-07-28

This dataset contains the data for the paper 'Using Multiple Instance Learning for Explainable Solar Flare Prediction'.

It consists of 10'000 spectrographs (bags) recorded by NASA's IRIS satellite with associated class labels AR (non-flaring active region) and PF (pre-flare active region). Each spectrograph consists of several hundred individual spectral pixels (instances).

The dataset is intended to explore the use of multiple instance learning for the prediction of solar flares. Even though class labels are only known at the level of the full spectrograph ('bag-level'), multiple instance learning allows to learn the association of individual spectra to each of the classes ('instance-level').

More information is provided in the paper and on the Zenodo page.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 3 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

Creative Commons Attribution 4.0 International

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • IRIS Multiple Instance Learning Dataset

1 variant name, as the archive lists them.

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