000 | nam a22 4500 | ||
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999 |
_c114375 _d114375 |
||
003 | OSt | ||
005 | 20190416134315.0 | ||
008 | 190130b ||||| |||| 00| 0 eng d | ||
020 | _a9781118879368 | ||
040 | _c | ||
082 |
_a658.40380 _bSHM |
||
100 |
_aShmueli, Galit _934955 |
||
245 |
_aData Mining for Business Analytics: Concepts, Techniques and Applications in R _cby Galit Shmueli, Peter C. Bruce, Inbal Yahav, Nitin R. Patel and Kenneth C. Lichtendahl |
||
260 |
_bJohn Wiley & Sons, Inc. _c2018 _aHoboken |
||
300 | _a544p | ||
500 | _aPart I: Preliminaries 1. Introduction 2. Overview of the data mining process Part II: Data Exploration and Dimension Reduction 3. Data visualization 4. Dimension reduction Part III: Performance Evaluation 5. Evaluating predictive performance Part IV: Prediction and Classification Methods 6. Multiple linear regression 7. k-Nearest Neighbors (kNN) 8. The Naive Bayes classifier 9. Classification and regression trees 10. Logistic regression 11. Neural nets 12. Discriminant analysis 13. Combining methods : ensembles and uplift modeling Part V: Mining Relationships Among Records 14. Association rules and collaborative filtering 15. Cluster analysis Part VI: Forecasting Time Series 16. Handling time series 17. Regression-based forecasting 18. Smoothing methods Part VII: Data Analytics 19. Social network analytics 20. Text mining Part VIII: Cases 21. Cases | ||
600 |
_aBusiness mathematics - Computer programs _937239 |
||
700 |
_aBruce, Peter C. _937240 |
||
700 |
_aYahav, Inbal _937241 |
||
700 |
_aPatel, Nitin R. _937242 |
||
700 |
_aLichtendahl, Kenneth C. _937243 |
||
942 |
_2ddc _cLB _k658.40380 _mSHM |