This section describes main characteristics of the magic data set and its attributes:
General information
MAGIC Gamma Telescope data set |
Type | Classification | Origin | Real world |
Features | 10 | (Real / Integer / Nominal) | (10 / 0 / 0) |
Instances | 19020 |
Classes | 2 |
Missing values? | No |
Attribute description
Attribute | Domain |
FLength | [4.2835, 334.177] |
FWidth | [0.0, 256.382] |
FSize | [1.9413, 5.3233] |
FConc | [0.0131, 0.893] |
FConc1 | [3.0E-4, 0.6752] |
FAsym | [-457.9161, 575.2407] |
FM3Long | [-331.78, 238.321] |
FM3Trans | [-205.8947, 179.851] |
FAlpha | [0.0, 90.0] |
FDist | [1.2826, 495.561] |
Class | {g, h} |
Additional information
This data set contains generated data to simulate registration of high energy gamma particles in a ground-based atmospheric Cherenkov gamma telescope using the imaging technique.
The data set was generated by a Monte Carlo program, Corsika, described in: D. Heck et al., CORSIKA, A Monte Carlo code to simulate extensive air showers, Forschungszentrum Karlsruhe FZKA 6019 (1998).
The task is to discriminate statistically images generated by primary gammas (signal, class label g) from the images of hadronic showers initiated by cosmic rays in the upper atmosphere (background, class label h).
Attribute information:
1. fLength: continuous # major axis of ellipse [mm]
2. fWidth: continuous # minor axis of ellipse [mm]
3. fSize: continuous # 10-log of sum of content of all pixels [in #phot]
4. fConc: continuous # ratio of sum of two highest pixels over fSize [ratio]
5. fConc1: continuous # ratio of highest pixel over fSize [ratio]
6. fAsym: continuous # distance from highest pixel to center, projected onto major axis [mm]
7. fM3Long: continuous # 3rd root of third moment along major axis [mm]
8. fM3Trans: continuous # 3rd root of third moment along minor axis [mm]
9. fAlpha: continuous # angle of major axis with vector to origin [deg]
10. fDist: continuous # distance from origin to center of ellipse [mm]
In this section you can download some files related to the magic data set:
- The complete data set already formatted in KEEL format can be downloaded from
here.
- A copy of the data set already partitioned by means of a 10-folds cross validation procedure can be downloaded from here.
- A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from here.
- The header file associated to this data set can be downloaded from here.
- This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning Repository. The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/MAGIC+Gamma+Telescope.
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