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Cookie akzeptieren![Gaber, Mohamed Medhat / Kieran Jay Edwards. Astronomy and Big Data - A Data Clustering Approach to Identifying Uncertain Galaxy Morphology. Springer International Publishing, 2014.](https://eichendorff21.de/cdata/Qy2rKqwpzmrjZ1edhrJq_vdTHnM=/300x0/9783319065984.png)
Mohamed Medhat Gaber / Kieran Jay Edwards
Astronomy and Big Data
- Springer International Publishing
- 2014
- Gebunden
- 120 Seiten
- ISBN 9783319065984
With the onset of massive cosmological data collection through media such as the Sloan Digital Sky Survey (SDSS), galaxy classification has been accomplished for the most part with the help of citizen science communities like Galaxy Zoo. Seeking the wisdom of the crowd for such Big Data processing has proved extremely beneficial. However, an analysis of one of the Galaxy Zoo morphological classification data sets has shown that a significant majority of all classified galaxies are labelled as ¿Uncertain¿. This book reports on how to use data mining, more specifically clustering, to identify galaxies that the public has shown some degree of uncertainty for as to
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