Data
solar_flare

solar_flare

active ARFF CC BY 4.0 Visibility: public Uploaded 22-12-2022 by Sebastian Fischer
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Data Description Predict the number of common solar flares. The database contains 3 classes, one for the number of times a certain type of solar flare occurred in a 24 hour period. Each instance represents captured features for 1 active region on the sun. Attribute Description 1. *class* - code for class (modified Zurich class) (A,B,C,D,E,F,H) 2. *largest_spot_size* - Code for largest spot size (X,R,S,A,H,K) 3. *spot_distribution* - Code for spot distribution (X,O,I,C) 4. *activity* - activity (1 = reduced, 2 = unchanged) 5. *evolution* - evolution (1 = decay, 2 = no growth, 3 = growth) 6. *previous_activity* - previous 24 hour flare activity code (1 = nothing as big as an M1, 2 = one M1, 3 = more activity than one M1) 7. *complex* - historically-complex (1 = Yes, 2 = No) 8. *complex_path* - whether region become historically complex on this pass across the sun's disk (1 = yes, 2 = no) 9. *area* - area (1 = small, 2 = large) 10. *area_largest* - area of the largest spot 11. *c_class_flares* - number of C-class flares production by this region in the following 24 hours (common flares), target feature 12. *m_class_flares* - number of M-class flares production by this region in the following 24 hours (moderate flares) 13. *x_class_flares* - number of X-class flares production by this region in the following 24 hours (severe flares)

11 features

c_class_flares (target)numeric8 unique values
0 missing
classnominal6 unique values
0 missing
largest_spot_sizenominal6 unique values
0 missing
spot_distributionnominal4 unique values
0 missing
activitynominal2 unique values
0 missing
evolutionnumeric3 unique values
0 missing
previous_activitynominal3 unique values
0 missing
complexnominal2 unique values
0 missing
complex_pathnominal2 unique values
0 missing
areanominal2 unique values
0 missing
area_largestnumeric1 unique values
0 missing
m_class_flares (ignore)numeric6 unique values
0 missing
x_class_flares (ignore)numeric3 unique values
0 missing

19 properties

1066
Number of instances (rows) of the dataset.
11
Number of attributes (columns) of the dataset.
0
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.
3
Number of numeric attributes.
8
Number 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.
4
Number of binary attributes.
36.36
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.48
Average class difference between consecutive instances.
0
Percentage of missing values.
0.01
Number of attributes divided by the number of instances.
27.27
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
72.73
Percentage of nominal attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: c_class_flares
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