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Data mining and business analytics with R
Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high...
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| Lenguaje: | eng |
| Publicado: |
Wiley
2013
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| Acceso en línea: | https://dx.doi.org/10.1002/9781118596289 http://cds.cern.ch/record/1568635 |
| _version_ | 1780931009490976768 |
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| author | Ledolter, Johannes |
| author_facet | Ledolter, Johannes |
| author_sort | Ledolter, Johannes |
| collection | CERN |
| description | Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data Mining |
| id | cern-1568635 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2013 |
| publisher | Wiley |
| record_format | invenio |
| spelling | cern-15686352021-04-21T22:33:03Zdoi:10.1002/9781118596289http://cds.cern.ch/record/1568635engLedolter, JohannesData mining and business analytics with RInformation Transfer and ManagementCollecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction and classification. Highlighting both underlying concepts and practical computational skills, Data MiningWileyoai:cds.cern.ch:15686352013 |
| spellingShingle | Information Transfer and Management Ledolter, Johannes Data mining and business analytics with R |
| title | Data mining and business analytics with R |
| title_full | Data mining and business analytics with R |
| title_fullStr | Data mining and business analytics with R |
| title_full_unstemmed | Data mining and business analytics with R |
| title_short | Data mining and business analytics with R |
| title_sort | data mining and business analytics with r |
| topic | Information Transfer and Management |
| url | https://dx.doi.org/10.1002/9781118596289 http://cds.cern.ch/record/1568635 |
| work_keys_str_mv | AT ledolterjohannes dataminingandbusinessanalyticswithr |