Discovering knowledge in data: An introduction to data mining (Record no. 1708)

MARC details
000 -LEADER
fixed length control field 02233nam a2200241 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250731101304.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250731b2014|||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781118873588
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Larose, Daniel T.
Relator term Author
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Larose, Chantal D.
Relator term Co-Author
245 ## - TITLE STATEMENT
Title Discovering knowledge in data: An introduction to data mining
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication New Jersey:
Name of publisher Wiley Data and Cybersecurity,
Year of publication 2014.
300 ## - PHYSICAL DESCRIPTION
Number of Pages xviii, 316p.
500 ## - GENERAL NOTE
General note The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before.<br/><br/>This book provides the tools needed to thrive in today’s big data world. The author demonstrates how to leverage a company’s existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. The reader will “learn data mining by doing data mining”. By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, Discovering Knowledge in Data, Second Edition remains the eminent reference on data mining .<br/><br/>The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis.<br/>Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization<br/>Offers extensive coverage of the R statistical programming language<br/>Contains 280 end-of-chapter exercises<br/>Includes a companion website for university instructors who adopt the book
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Introduction to Data Mining
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Data Preprocessing and Exploratory Data Analysis
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Univariate Statistical Analysis and Multivariate Statistics
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://ieeexplore.ieee.org/servlet/opac?bknumber=10066951
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type e-Books
Holdings
Withdrawn status Lost status Damaged status Not for loan Permanent Location Current Location Shelving location Coded location qualifier Full call number Accession Number Koha item type
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