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---+ [[IvoaKDDguide][IVOA KDD-IG: A user guide for Data Mining in Astronomy]]

---++ 8: Links: Books, papers, websites

There are a large number of books, papers, and websites about data mining. This section does not aim to exhaustively list everything, but to point to those resources that are most useful for astronomy. We start with links specific to astronomy, followed by more general data mining links that are useful to astronomers.

---+++ Links specific to Astronomy

---++++ Books

   * *Way M., Scargle J.D., Ali K.M., Srivastava A.N.* (eds.), Advances in Machine Learning and Data Mining for Astronomy (Data Mining and Knowledge Discovery Series, CRC Press, Boca Raton, FL, 2012)

---++++ Review Papers

   * *Graham, M.*, _The Art of Data Science_, arXiv/1106.3305; invited talk at Astrostatistics and Data Mining in Large Astronomical Databases workshop, La Palma, Spain, 30 May - 3 June 2011, to appear in Springer Series on Astrostatistics
   * *Ball N.M. & Brunner R.J.*, _Data Mining and Machine Learning in Astronomy_, International Journal of Modern Physics D 19 (7) 1049-1106 (2010); arXiv/0906.2173; http://ned.ipac.caltech.edu/level5/March11/Ball/frames.html
   * *Borne K.D.*, _Astroinformatics: data-oriented astronomy research and education_, Earth Science Informatics 3(1-2): 5-17 (2010), http://dx.doi.org/10.1007/s12145-010-0055-2
   * *Feigelson E.D.*, _Cross-disciplinary research in astronomy_, Proceedings of Science (2010)
   * *Pesenson M.Z, Pesenson I.Z. & !McCollum B.*, _The Data Big Bang and the Expanding Digital Universe: High-Dimensional, Complex and Massive Data Sets in an Inflationary Epoch_ (2010)
   * *Borne K.D.*, _Scientific Data Mining in Astronomy_, Data Mining and Knowledge Discovery Series, Taylor & Francis: CRC Press, Boca Raton, FL, Ch. 5, pp. 91–114 (2009); arXiv/0911.0505

   * *Hassan A. & Fluke C.J.*, PASA 28 150 (2011): _Scientific Visualization in Astronomy: Towards the Petascale Astronomy Era_

   * *Tagliaferri R., et al.*, _Neural networks in astronomy_, Neural Networks 16 297 (2003)
   * Vistas in Astronomy 38 (1994), Special Issue on Artificial Neural Networks in Astronomy
   * *Miller A.S.*, _A Review of Neural Network Applications in Astronomy_, Vistas in Astronomy 36 141-161 (1993)

   * *Charbonneau P.*, _Genetic Algorithms in Astronomy and Astrophysics_, !ApJS 101 309 (1995)

---++++ White Papers

   * *Borne K.D. et al.*, _Astroinformatics: A 21st Century Approach to Astronomy_, white paper submitted to the US Astro 2010 decadal review of astronomy; http://www8.nationalacademies.org/astro2010/DetailFileDisplay.aspx?id=455
   * *Ferguson H.C., et al.*, _Astronomical Data Reduction and Analysis for the Next Decade_, Astro2010; http://www8.nationalacademies.org/astro2010/DetailFileDisplay.aspx?id=426
   * *Loredo T.J., et al.*, _The Astronomical Information Sciences: A Keystone for 21st-Century Astronomy_, Astro2010; http://www8.nationalacademies.org/astro2010/DetailFileDisplay.aspx?id=439

   * *Ball N.M. & Schade D.*, _Astroinformatics in Canada_, white paper submitted to the Canadian Long Range Plan in Astronomy (LRP 2010); http://www.casca.ca/lrp2010/Docs/LRPReports/astroinformatics_lrp.pdf
   * *Dursi L.J.*, _Canadian Astronomical Computing, Data, and Network Facilities_, LRP2010; http://www.casca.ca/lrp2010/Docs/LRPReports/CDandN_WP.pdf

---++++ Websites

   * https://asaip.psu.edu --- Penn State Astrostatistics and Astroinformatics portal
   * http://ivoa.net/newsletter --- Newsletter of the International Virtual Observatory, including links to useful software, and VO-enabled science
   * http://www.practicalastroinformatics.org --- Astroinformatics

   * http://dame.dsf.unina.it --- DAME, Data Mining and Exploration, a web-based distributed data mining infrastructure
   * http://canfar.phys.uvic.ca --- CANFAR, a cloud computing environment for astronomers, designed to provide the infrastructure on which to build a data processing project

   * http://cftd.info --- Berkeley Centre for Time Domain Informatics
   * http://cmmlu.wikispaces.com --- Cosmology meets machine learning

   * http://astrostatistics.psu.edu  --- Penn State Center for Astrostatistics
   * http://www.stat.cmu.edu/~inca --- International Computational Astrostatistics Group
   * http://hea-www.harvard.edu/AstroStat --- California/Boston/Smithsonian Astrostatistics Collaboration

---++++ Blogs

   * http://astrodatamining.net --- Data Mining in Astronomy
   * http://groundtruth.info/AstroStat/slog --- Astrostatistics
   * http://astrocompute.wordpress.com --- Astronomy Computing Today
   * http://www.astrobetter.com --- !AstroBetter

---++++ Podcast

   * http://365daysofastronomy.org/2012/03/06/march-6th-astroinformatics --- 365 Days of Astronomy episode on Astroinformatics

---+++ General Data Mining Links

---++++ Books

   * *Hey T., Tansley S. & Talle K.* (eds.), _The Fourth Paradigm: Data-Intensive Scientific Discovery_ (Microsoft Research, Redmond, WA, 2009)
   * *Kamath C.*, _Scientific Data Mining: A Practical Perspective_ (Society for Industrial and Applied Mathematics, Philadelphia, PA, 2009)
   * *Hastie T., Tibshirani R. & Friedman J.*, _The Elements of Statistical Learning: Data Mining, Inference, and Prediction_, Springer Series in Statistics, 2nd edn. (Springer, New York, NY, 2009)
   * *Witten I.H. & Frank E.*, _Data Mining: Practical Machine Learning Tools and Techniques_, Morgan Kaufmann Series in Data Management Systems, 2nd edn. (Morgan Kaufmann, San Francisco, CA, 2005)
   * *Bishop C.M.*, _Pattern Recognition and Machine Learning_ (Springer, New York, NY, 2007)

   * *Gregory P.*, _Bayesian Logical Data Analysis for the Physical Sciences_ (Cambridge University Press, Cambridge, UK, 2005)

   * *Tufte, E.R.*, _The Visual Display of Quantitative Information_, 2nd edn. (Graphics Press, Cheshire, CT, 2001)

   * *Bishop C.M.*, _Neural Networks for Pattern Recognition_ (Oxford University Press, Oxford, UK, 1995)
   * *Ripley B.D.*, _Pattern Recognition and Neural Networks_ (Cambridge University Press, Cambridge, UK, 2008)

---++++ Papers

   * *Hand D.J.*, Statistical Science 21 1 (2006): _Classifier Technology and the Illusion of Progress_
   * *Kamath C.*, Journal of Physics Conference Series 125 012094 (2008): _Sapphire: Experiences in Scientific Data Mining_

---++++ Websites

   * http://www.kdnuggets.com --- General data mining website with numerous resources
   * http://www.kdd.org --- Knowledge discovery in databases, a more broadly-based site on this group's interest
   * http://www.autonlab.org/tutorials --- Statistical Data Mining Tutorials
   * http://en.wikipedia.org/wiki/Category:Machine_learning --- Wikipedia has many useful introductory articles for the non-specialist

---++++ Software

   * http://www.cs.waikato.ac.nz/ml/weka --- WEKA, a commonly used data mining environment
   * http://rapid-i.com --- !RapidMiner, along with WEKA, the most commonly used data mining software
   * http://www.r-project.org --- R, widely used in statistics, including astrostatistics
   * http://mloss.org/software --- Open-source machine learning software


<br>

-- IVOA.NickBall - 19 Mar 2011
<br>
-- IVOA.NickBall - 23 Sep 2011
<br>
-- IVOA.NickBall - 05 Oct 2011
<br>
-- IVOA.NickBall - 07 May 2012

<br>

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Topic revision: r12 - 2012-05-07 - NickBall
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