Handbook of Statistical Analysis and Data Mining Applications

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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. • Includes input by practitioners for practitioners • Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models • Contains practical advice from successful real-world implementations • Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions • Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Author(s): Robert Nisbet, Gary Miner, Ken Yale
Edition: 2
Publisher: Academic Press
Year: 2017

Language: English
Commentary: True PDF
Pages: 822
Tags: Machine Learning; Algorithms; Data Analysis; Deep Learning; Reinforcement Learning; Regression; Data Mining; Big Data; Classification; Predictive Models; Statistics; Model Evaluation; Feature Extraction; Generalized Additive Models; Fraud Detection