MARC details
| 000 -LEADER |
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| fixed length control field |
02708nam a2200253Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
NULRC |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250520102804.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250520s9999 xx 000 0 und d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781118729274 |
| 040 ## - CATALOGING SOURCE |
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| Transcribing agency |
NULRC |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
HF 5548.2 .S44 2016 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Shmueli, Galit |
| Relator term |
author |
| 245 #0 - TITLE STATEMENT |
|---|
| Title |
Data mining for business analytics : |
| Remainder of title |
concepts, techniques, and applications with XLMiner / |
| Statement of responsibility, etc. |
Galit Shmueli, Peter C. Bruce and Nitin R. Patel |
| 250 ## - EDITION STATEMENT |
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| Edition statement |
THIRD EDITION. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Hoboken, New Jersey : |
| Name of publisher, distributor, etc. |
John Wiley & Son, Inc., |
| Date of publication, distribution, etc. |
c2016 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxx, 514 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
26 cm. |
| 365 ## - TRADE PRICE |
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| Price amount |
USD106.74 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Includes bibliographical references and index. |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Part 1. Preliminaries -- 1. Introduction -- 2. Overview of the data mining process -- Part 2. Data exploration and dimension reduction -- 3. Data visualization -- 4. Dimension reduction -- Part 3. Performance evaluation -- 5. Evaluating predictive performance -- Part 4. Prediction and classification methods -- 6. Multiple linear regression -- 7. k-Nearest-Neighbors (k-NN) -- 8. teh 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 5. Mining relationships among records -- 14. Association rules and collaborative filtering -- 15. Cluster analysis -- Part 6. Forecasting time series -- 16. Handling time series -- 17. Regression-based forecasting -- 18. Smoothing methods -- Part 7. Data analytics -- 19. Social network analytics -- 20. text mining -- Part 8. Cases -- 21. Cases. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
COMPUTER FILE |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Bruce, Peter C.;Patel, Nitin R. |
| Relator term |
co-author;co-author |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Books |
