Analiza podataka — разлика између измена

'''Analiza podataka'''<ref name=Fayyad>{{cite web | last = Fayyad | first = Usama |author2 = Gregory Piatetsky-Shapiro |author3= Padhraic Smyth | title = From Data Mining to Knowledge Discovery in Databases | year = 1996 | url = http://www.kdnuggets.com/gpspubs/aimag-kdd-overview-1996-Fayyad.pdf | accessdate = 17. 12. 2008.}}</ref> ({{jez-en|data analysis|el}}) relativno je mlado i interdisciplinarno polje [[informatika|informatike]],<ref name="acm">{{cite web |url=http://www.sigkdd.org/curriculum.php |title=Data Mining Curriculum |publisher=Association for Computing Machinery, SIGKDD |date=30. 4. 2006. |accessdate=28. 10. 2011. |archive-url=https://web.archive.org/web/20111028082122/http://www.sigkdd.org/curriculum.php |archive-date=28. 10. 2011 |dead-url=yes |df= }}</ref><ref name=brittanica>{{cite web | last = Clifton | first = Christopher | title = Encyclopædia Britannica: Definition of Data Mining | year = 2010 | url = http://www.britannica.com/EBchecked/topic/1056150/data-mining | accessdate = 9. 12. 2010.}}</ref> koje se bavi otkrivanjem novih obrazaca u velikim skupovima [[podatak]]a. Ona koristi metode koji su u preseku [[вјештачка интелигенција|veštačke inteligencije]], [[mašinsko učenje|mašinskog učenja]], [[statistika|statistike]], i [[База података|sistema baza podataka]].<ref name="acm" /> Sveukupni cilj analize podataka je ekstrakcija znanja iz postojećih podataka i trasformacija u oblik podesan za dalju upotrebu.<ref name="acm" /> Treba imati u vidu da je [[rudarenje podataka]] ({{jez-en|data mining|el}}) samo jedna od tehnika analize podataka koja se oslanja na modelovanje i otkrivanje znanja za prediktivne, a ne čisto deskriptivne svrhe, dok [[poslovna inteligencija]] ({{jez-en|business intelligence|el}}) obuhvata analizu podataka koja se u velikoj meri oslanja na agregaciju, fokusirajući se uglavnom na poslovne informacije.<ref>[https://web.archive.org/web/20171018181046/https://spotlessdata.com/blog/exploring-data-analysis Exploring Data Analysis]</ref>

* Cabena, Peter, Pablo Hadjnian, Rolf Stadler, Jaap Verhees and Alessandro Zanasi (1997). ''Discovering Data Mining: From Concept to Implementation''. Prentice Hall,. ISBN 978-0-13-743980-5.

* Feldman, Ronen and James Sanger. ''The Text Mining Handbook''. Cambridge University Press,. ISBN 978-0-521-83657-9.

* Hastie Trevor, Robert Tibshirani and Jerome Friedman (2001). ''The Elements of Statistical Learning: Data Mining, Inference, and Prediction''. Springer,. ISBN 978-0-387-95284-0.

* Liu, Bing (2007). ''Web Data Mining: Exploring Hyperlinks, Contents and Usage Data.'' Springer Verlag,. ISBN 978-3-540-37881-5.

* {{cite journal|last=Murphy|first=Chris|date= 16. 5. 2011|title=Is Data Mining Free Speech? |journal=InformationWeek | publisher = UBM plc |pages=12 }}

* Nisbet, Robert, John Elder, Gary Miner (2009). ''Handbook of Statistical Analysis & Data Mining Applications''. Academic Press / Elsevier. ISBN {{page|year=|isbn=978-0-12-374765-5|pages=}}

* Poncelet, Pascal, Florent Masseglia and Maguelonne Teisseire, editors (October 2007). "Data Mining Patterns: New Methods and Applications", ''Information Science Reference''. ISBN {{page|year=|isbn=978-1-59904-162-9|pages=}}.

* Pang-Ning Tan, Michael Steinbach and Vipin Kumar (2005). ''Introduction to Data Mining''. ISBN {{page|year=|isbn=978-0-321-32136-7|pages=}}

* Sergios Theodoridis, Konstantinos Koutroumbas (2009). ''Pattern Recognition'', 4th Edition. Academic Press. ISBN {{page|year=|isbn=978-1-59749-272-0|pages=}}.

* {{Cite book |ref= harv|last1last=Witten|first1first=Ian H.|last2=Frank|first2=Eibe|last3=Hall|first3=Mark A.|title=Data Mining: Practical Machine Learning Tools and Techniques|edition=3|year=2011|publisher=Elsevier|isbn=978-0-12-374856-0|pages=}} (See also Free Weka software.)