This was the most powerful flare measured with modern methods, classified as an X28.
Visualization and Data Mining in an 3D Immersive Environment: Summer Project 2003.The Solar and Heliospheric Observatory spacecraft captured this image of a solar flare as it erupted from the sun early on Nov 4, 2003. School of Computer Science & Engineering Hebrew University.Ĭ. A Bayesian Approach to Structure Discovery in Bayesian Networks. An Integrated Framework for Learning and Reasoning. Enhancing Supervised Learning with Unlabeled Data. Instance-Based Classification by Emerging Patterns. Jinyan Li and Guozhu Dong and Kotagiri Ramamohanarao. Proceedings of the Fourth European Conference on Principles and Practice of Knowledge Discovery in Databases. DeEPs: A New Instance-based Discovery and Classification System. Jinyan Li and Guozhu Dong and Kotagiri Ramamohanarao and Limsoon Wong. X-class flares production by this region in the following 24 hours (severe flares) Number M-class flares production by this region in the following 24 hours (moderate flares) Numberġ3. C-class flares production by this region in the following 24 hours (common flares) Numberġ2. Did region become historically complex on this pass across the sun's disk (1 = yes, 2 = no)įrom all these predictors three classes of flares are predicted, which are represented in the last three columns.ġ1. Previous 24 hour flare activity code (1 = nothing as big as an M1, 2 = one M1, 3 = more activity than one M1)ħ. Evolution (1 = decay, 2 = no growth, 3 = growth)Ħ. Code for largest spot size (X,R,S,A,H,K)ĥ. Code for class (modified Zurich class) (A,B,C,D,E,F,H)Ģ. The second section (flare.data2) has had much more error correction applied to the it, and has consequently been treated as more reliable.ġ. The data are divided into two sections. Each instance represents captured features for 1 active region on the sun. The database contains 3 potential classes, one for the number of times a certain type of solar flare occured in a 24 hour period. Click here to try out the new site.ĭownload: Data Folder, Data Set DescriptionĪbstract: Each class attribute counts the number of solar flares of a certain class that occur in a 24 hour period Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns.
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