Published March 21, 2022
| Version v1
Dataset
Open
IRIS Multiple Instance Learning Dataset
Description
This dataset contains the data for the paper 'Using Multiple Instance Learning for Explainable Solar Flare Prediction' (arxiv pre-print) . It comes as a compressed Python Numpy-File and contains the following variables:
| Name | Shape | Description |
|---|---|---|
| data | (10'000, 1100, 240) | 10'000 Bags of zero-padded spectrograms |
| data_scaled | (10'000, 1100, 240) | Like data, but standard-scaled |
| masks | (10'000, 1100) | Masks that indicate where spectrograms have been zero-padded |
| groups | (10'000,) | Observation group the bag is assigned to |
| obs_ids | (10'000,) | Observation ID the bag is assigned to |
| obs_classes | (10'000,) | Observation class (AR/PF) the bag is assigned to |
| raster_pos | (10'000,) | Raster position number the bag was taken from (always 0 for sit-and-stare) |
| folds | (10'000,) | Validation fold for the particular observation group |
To load the e.g. the variable 'data', use Python and Numpy:
import numpy as np
f = np.load("IRISMIL_dataset_10000_bags.npz", allow_pickle=True)
f['data']
Files
Files
(9.4 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:118f1d16760952436b3cd77228b972c8
|
9.4 GB | Download |