9780470908747 - Discovering Knowledge in Data: An Introduction to Data Mining di Larose, Daniel T.; Larose, Chantal D. (31 risultati)

Condizione: Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: second ] Publisher: Wiley Pub Date: 6/30/2014 Binding: Hardcover Pages: 336 second edition.

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Condizione: New.

Condizione: New. pp. 336 2nd Edition.

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Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Condizione: New. pp. 336.

Condizione: New.

Condizione: New. In.

Hardcover. Condizione: new. Hardcover. 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. This book provides the tools needed to thrive in todays big data world. The author demonstrates how to leverage a companys 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. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis.Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and VisualizationOffers extensive coverage of the R statistical programming languageContains 280 end-of-chapter exercisesIncludes a companion website for university instructors who adopt the book 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Hardback. Condizione: New. 2nd. 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. 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. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis.Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and VisualizationOffers extensive coverage of the R statistical programming languageContains 280 end-of-chapter exercisesIncludes a companion website for university instructors who adopt the book.

Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New. 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. Series: Wiley Series on Methods and Applications in Data Mining. Num Pages: 336 pages, illustrations. BIC Classification: UNF. Category: (P) Professional & Vocational. Dimension: 236 x 164 x 25. Weight in Grams: 632. . 2014. 2nd Edition. Hardcover. . . . .

Hardcover. Condizione: Brand New. 2nd har/psc edition. 316 pages. 9.75x6.50x1.00 inches. In Stock.

Condizione: New. 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. Series: Wiley Series on Methods and Applications in Data Mining. Num Pages: 336 pages, illustrations. BIC Classification: UNF. Category: (P) Professional & Vocational. Dimension: 236 x 164 x 25. Weight in Grams: 632. . 2014. 2nd Edition. Hardcover. . . . . Books ship from the US and Ireland.

Gebunden. Condizione: New. Daniel T. Larose earned his PhD in Statistics at the University of Connecticut. He is Professor of Mathematical Sciences and Director of the Data Mining programs at Central Connecticut State University. His consulting clients have included Microsoft, Forbes.

Hardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Hardback. Condizione: New. 2nd. 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. 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. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis.Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and VisualizationOffers extensive coverage of the R statistical programming languageContains 280 end-of-chapter exercisesIncludes a companion website for university instructors who adopt the book.

Buch. Condizione: Neu. Neuware - 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. 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.\* The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis.\* Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization\* Offers extensive coverage of the R statistical programming language\* Contains 280 end-of-chapter exercises\* Includes a companion website with further resources for all readers, and Powerpoint slides, a solutions manual, and suggested projects for instructors who adopt the book.

Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 720.

Hardcover. Condizione: Brand New. 2nd har/psc edition. 316 pages. 9.75x6.50x1.00 inches. In Stock. This item is printed on demand.

Hardcover. Condizione: new. Hardcover. 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. This book provides the tools needed to thrive in todays big data world. The author demonstrates how to leverage a companys 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. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis.Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and VisualizationOffers extensive coverage of the R statistical programming languageContains 280 end-of-chapter exercisesIncludes a companion website for university instructors who adopt the book 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.