OpenML
Viewing-Solar-Flares

Viewing-Solar-Flares

active ARFF CC BY-NC-SA 4.0 Visibility: public Uploaded 23-03-2022 by Dustin Carrion
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  • Computer Systems Machine Learning
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Context The subject of this dataset is multi-instrument observations of solar flares. There are a number of space-based instruments that are able to observe solar flares on the Sun; some instruments observe the entire Sun all the time, and some only observe part of the Sun some of the time. We know roughly where flares occur on the Sun but we don't know when they will occur. In this respect solar flares resemble earthquakes on Earth. This dataset is a catalog of which solar flares have been observed by currently operational space-based solar observatories. Content It includes that start time and end time of each solar flare from 1 May 2010 to 9 October 2017 and which instrument(s) they were observed by. It was collected by doing a retrospective analysis of the known pointing of seven different instruments with the location and times of 12,455 solar flares. Acknowledgements The dataset was compiled by Dr. Ryan Milligan based on publicly available data and are freely distributed. The citation of relevance is https://arxiv.org/abs/1703.04412. Inspiration This dataset represents the first attempted evaluation of how well space-based instrumentation co-ordinate when it comes to observing solar flares. We are particularly interested in understanding how often combinations of instruments co-observe the same flare. The ultimate purpose is to try to find strategies that optimize the scientific return on solar flare data given the limited space-based instrument resources available. More often than not, our greatest understanding of these explosive events come through simultaneous observations made by multiple instruments.

17 features

Sol (ignore)string12397 unique values
0 missing
JJJ_Startstring12397 unique values
0 missing
JJJ_Peakstring12058 unique values
0 missing
JJJ_Endstring12367 unique values
0 missing
JJJ_Classstring271 unique values
0 missing
HHH_X-posnumeric11766 unique values
0 missing
HHH_y-posnumeric12142 unique values
0 missing
AAA_lonumeric8 unique values
0 missing
AAA_hinumeric8 unique values
0 missing
AAA_X-posnumeric6890 unique values
0 missing
AAA_Y-posnumeric6867 unique values
0 missing
AAAnumeric2 unique values
0 missing
BBBnumeric2 unique values
0 missing
CCCnumeric2 unique values
0 missing
DDDnumeric2 unique values
0 missing
EEEnumeric2 unique values
0 missing
FFFnumeric2 unique values
0 missing
GGGnumeric2 unique values
0 missing

19 properties

12455
Number of instances (rows) of the dataset.
17
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
13
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
76.47
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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