Handbook of statistical analysis and data mining applications / Robert Nisbet, Gary Miner, Ken Yale ; guest authors of selected chapters, John Elder, Andy Peterson.
Material type: TextPublisher: London : Academic Press, [2018]Edition: 2nd edDescription: xxix, 792 pages : color illustrations, charts (chiefly color), portraits (some color) ; 25 cmContent type:- text
- unmediated
- volume
- 9780124166325
- 0124166326
- QA76.9 .D34 N58 2018
- Cataloging Notes: 20241116 STAMIU-0199STAMIU-0199
Item type | Current library | Collection | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|
Book | AMREF INTERNATIONAL UNIVERSITY (AMIU) LIBRARY General Stacks | Non-fiction | QA76.9 .D34 N58 2018 (Browse shelf(Opens below)) | Available | 20657 | ||
Book | AMREF INTERNATIONAL UNIVERSITY (AMIU) LIBRARY General Stacks | Non-fiction | QA76.9 .D34 N58 2018 (Browse shelf(Opens below)) | Available | 20658 |
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QA76.9.D3 R5494 2021 Data engineering on Azure / | QA76.9 .D34 H36 2012 Data mining: concepts and techniques / | QA76.9 .D34 N58 2018 Handbook of statistical analysis and data mining applications / | QA76.9 .D34 N58 2018 Handbook of statistical analysis and data mining applications / | QA76.9 .D34 W56 2017 Data mining : practical machine learning tools and techniques / | QA76.9 .D37M35 2023 CISCO DATA CENTER FUNDAMENTALS bridging the gap to CCNP / | QA 76.9 .M36 2021 Comptia cybersecurity analyst (cysa+) cs0-002 cert guide / |
Includes bibliographical references and index.
History of phases of data analysis, basic theory, and the data mining process -- The algorithms and methods in data mining and predictive analytics and some domain areas -- Tutorials and case studies -- Models ensembles, model complexity; using the right model for the right use, significance, ethics, and the future and advanced processes.
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas-from science and engineering, to medicine, academia and commerce.
Cataloging Notes: 20241116 STAMIU-0199STAMIU-0199
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