Advances in Machine Learning and Data Mining for Astronomy
Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book's introd…
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- Full title :Advances in Machine Learning and Data Mining for Astronomy
Summary
Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book's introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.
Read More ↓Edition Statements
- Publication Date:2012
- Edition:1
Publication Statements
- Publisher(s):Taylor and Francis
- Place of Publication:Hoboken
- Language:eng
- Publication Date:2012
The Physical Object
- Description:1 online resource (720 Seiten)
Edition Identifiers
- ISBN:9781439841730, 143984173X, 9781439841747, 1439841748
- oclc:ocn880404850
- LC Classification:QB51.3.E43 A386 2012
- Dewey Decimal:522.85631
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