Data preparation for data mining using SAS:
Are you a data mining analyst, who spends up to 80% of your time assuring data quality, then preparing that data for developing and deploying predictive models? And do you find lots of literature on data mining theory and concepts, but when it comes to practical advice on developing good mining view...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam Boston
Morgan Kaufmann Publishers
© 2007
|
| Schriftenreihe: | Morgan Kaufmann series in data management systems
|
| Schlagworte: | |
| Online-Zugang: | FLA01 Volltext |
| Zusammenfassung: | Are you a data mining analyst, who spends up to 80% of your time assuring data quality, then preparing that data for developing and deploying predictive models? And do you find lots of literature on data mining theory and concepts, but when it comes to practical advice on developing good mining views find little how to information? And are you, like most analysts, preparing the data in SAS? This book is intended to fill this gap as your source of practical recipes. It introduces a framework for the process of data preparation for data mining, and presents the detailed implementation of each step in SAS. In addition, business applications of data mining modeling require you to deal with a large number of variables, typically hundreds if not thousands. Therefore, the book devotes several chapters to the methods of data transformation and variable selection. FEATURES * A complete framework for the data preparation process, including implementation details for each step. * The complete SAS implementation code, which is readily usable by professional analysts and data miners. * A unique and comprehensive approach for the treatment of missing values, optimal binning, and cardinality reduction. * Assumes minimal proficiency in SAS and includes a quick-start chapter on writing SAS macros. * CD includes dozens of SAS macros plus the sample data and the program for the book's case study |
| Beschreibung: | Includes bibliographical references (pages 373-374) and index |
| Beschreibung: | 1 online resource (xxi, 399 pages) illustrations |
| ISBN: | 9780080491004 0080491006 |
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| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
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| dewey-search | 006.3/12 |
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| discipline | Informatik |
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| id | DE-604.BV046123906 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:35:49Z |
| institution | BVB |
| isbn | 9780080491004 0080491006 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031504359 |
| oclc_num | 156780417 |
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| physical | 1 online resource (xxi, 399 pages) illustrations |
| psigel | ZDB-33-ESD ZDB-33-ESD FLA_PDA_ESD |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Morgan Kaufmann Publishers |
| record_format | marc |
| series2 | Morgan Kaufmann series in data management systems |
| spelling | Refaat, Mamdouh Verfasser aut Data preparation for data mining using SAS Mamdouh Refaat Amsterdam Boston Morgan Kaufmann Publishers © 2007 1 online resource (xxi, 399 pages) illustrations txt rdacontent c rdamedia cr rdacarrier Morgan Kaufmann series in data management systems Includes bibliographical references (pages 373-374) and index Are you a data mining analyst, who spends up to 80% of your time assuring data quality, then preparing that data for developing and deploying predictive models? And do you find lots of literature on data mining theory and concepts, but when it comes to practical advice on developing good mining views find little how to information? And are you, like most analysts, preparing the data in SAS? This book is intended to fill this gap as your source of practical recipes. It introduces a framework for the process of data preparation for data mining, and presents the detailed implementation of each step in SAS. In addition, business applications of data mining modeling require you to deal with a large number of variables, typically hundreds if not thousands. Therefore, the book devotes several chapters to the methods of data transformation and variable selection. FEATURES * A complete framework for the data preparation process, including implementation details for each step. * The complete SAS implementation code, which is readily usable by professional analysts and data miners. * A unique and comprehensive approach for the treatment of missing values, optimal binning, and cardinality reduction. * Assumes minimal proficiency in SAS and includes a quick-start chapter on writing SAS macros. * CD includes dozens of SAS macros plus the sample data and the program for the book's case study SAS (Computer file) SAS (Computer file) fast COMPUTERS / Database Management / Data Mining bisacsh Data mining fast Data mining Erscheint auch als Druck-Ausgabe 0123735777 Erscheint auch als Druck-Ausgabe 9780123735775 http://www.sciencedirect.com/science/book/9780123735775 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Refaat, Mamdouh Data preparation for data mining using SAS SAS (Computer file) SAS (Computer file) fast COMPUTERS / Database Management / Data Mining bisacsh Data mining fast Data mining |
| title | Data preparation for data mining using SAS |
| title_auth | Data preparation for data mining using SAS |
| title_exact_search | Data preparation for data mining using SAS |
| title_full | Data preparation for data mining using SAS Mamdouh Refaat |
| title_fullStr | Data preparation for data mining using SAS Mamdouh Refaat |
| title_full_unstemmed | Data preparation for data mining using SAS Mamdouh Refaat |
| title_short | Data preparation for data mining using SAS |
| title_sort | data preparation for data mining using sas |
| topic | SAS (Computer file) SAS (Computer file) fast COMPUTERS / Database Management / Data Mining bisacsh Data mining fast Data mining |
| topic_facet | SAS (Computer file) COMPUTERS / Database Management / Data Mining Data mining |
| url | http://www.sciencedirect.com/science/book/9780123735775 |
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