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LEADER 00000cam  2200589Ii 4500 
001    874011854 
003    OCoLC 
005    20190118062808.1 
006    m     o  d         
007    cr unu|||||||| 
008    140320s2012    flua    ob    000 0 eng d 
010    2012008925 
019    974301192|a1066451774 
020    1466503963 
020    9781466503960 
020    |z9781466503960 
020    9781466503984 
020    146650398X 
035    (OCoLC)874011854|z(OCoLC)974301192|z(OCoLC)1066451774 
037    CL0500000404|bSafari Books Online 
040    UMI|beng|epn|erda|cUMI|dCOO|dOCLCO|dOCLCA|dDEBBG|dDEBSZ
       |dOCLCQ|dOCLCO|dOCLCF|dOCLCO|dOCLCQ|dVT2|dCEF 
049    MAIN 
050  4 HF5415.126|b.P885 2012 
082 00 658.4/0302855133|223 
100 1  Putler, Daniel S.|0http://id.loc.gov/authorities/names/
       n85075133 
245 10 Customer and business analytics :|bapplied data mining for
       business decision making using R /|cDaniel S. Putler, 
       Robert E. Krider. 
264  1 Boca Raton, FL :|bCRC Press,|c2012. 
300    1 online resource (xxvi, 285 pages) :|billustrations. 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
490 1  Chapman & Hall/CRC the R series. 
504    Includes bibliographical references (pages 283-285). 
505 0  Part I I Purpose and Process -- chapter 1 Database 
       Marketing and Data Mining -- chapter 2 A Process Model for
       Data Mining—CRISP-DM -- part II II Predictive 
       Modeling Tools -- chapter 3 Basic Tools for Understanding 
       Data -- chapter 4 Multiple Linear Regression -- chapter 5 
       Logistic Regression -- chapter 6 Lift Charts -- chapter 7 
       Tree Models -- chapter 8 Neural Network Models -- chapter 
       9 Putting It All Together -- part III III Grouping Methods
       -- chapter 10 Ward’s Method of Cluster Analysis and
       Principal Components -- chapter 11 K-Centroids 
       Partitioning Cluster Analysis. 
520 3  Customer and Business Analytics: Applied Data Mining for 
       Business Decision Making Using R explains and demonstrates,
       via the accompanying open-source software, how advanced 
       analytical tools can address various business problems. It
       also gives insight into some of the challenges faced when 
       deploying these tools. Extensively classroom-tested, the 
       text is ideal for students in customer and business 
       analytics or applied data mining as well as professionals 
       in small- to medium-sized organizations. 
588 0  Print version record. 
650  0 Database marketing.|0http://id.loc.gov/authorities/
       subjects/sh90004314 
650  0 Data mining.|0http://id.loc.gov/authorities/subjects/
       sh97002073 
650  0 Decision making|xData processing.|0http://id.loc.gov/
       authorities/subjects/sh2008102118 
650  0 R (Computer program language)|0http://id.loc.gov/
       authorities/subjects/sh2002004407 
650  0 Database management.|0http://id.loc.gov/authorities/
       subjects/sh85035848 
655  4 Electronic books. 
700 1  Krider, Robert E.|0http://id.loc.gov/authorities/names/
       n2012019101 
776 08 |iPrint version:|aPutler, Daniel S.|tCustomer and business
       analytics.|dBoca Raton, FL : CRC Press, 2012
       |z9781466503960|w(DLC)  2012008925|w(OCoLC)756596227. 
830  0 Chapman & Hall/CRC the R series (CRC Press)|0http://
       id.loc.gov/authorities/names/no2011138179 
990    ProQuest Safari|bO'Reilly Safari Learning Platform: 
       Academic edition|c2019-01-18|yMaster record variable 
       field(s) change: 505|5OH1 
990    ProQuest Safari|bO'Reilly Safari Learning Platform: 
       Academic edition|c2018-10-22|yNew collection 
       ProQuest.ormac|5OH1 
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