Handbook Of Statistical Analysis And Data Mining Applications

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Handbook of Statistical Analysis and Data Mining Applications

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Author by : Robert Nisbet
Languange Used : English, France, Spanish, Italia and chinese
Page : 822
Isbn : 0124166458
Identifier : 9780124166455
Release : 2017-11-09
Publisher by : Elsevier
Category : Mathematics
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Description : Read Now Handbook Of Statistical Analysis And Data Mining Applications by Robert Nisbet and you can download with pub, pdf, txt, doc, and more file format with free account. 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

Handbook of Statistical Analysis and Data Mining Applications

Download Handbook Of Statistical Analysis And Data Mining Applications Book or Ebook File with PDF Epub Audio and Full format File

Author by : Robert Nisbet
Languange Used : English, France, Spanish, Italia and chinese
Page : 864
Isbn : 9780080912035
Identifier : 0080912036
Release : 2009-05-14
Publisher by : Academic Press
Category : Mathematics
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Description : Read Now Handbook Of Statistical Analysis And Data Mining Applications by Robert Nisbet and you can download with pub, pdf, txt, doc, and more file format with free account. the handbook of statistical analysis and data mining applications 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 one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. use this book 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 industries - from science and engineering, to medicine, academia and commerce. this handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. written "by practitioners for practitioners" non-technical explanations build understanding without jargon and equations tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models practical advice from successful real-world implementations includes extensive case studies, examples, ms powerpoint slides and datasets cd-dvd with valuable fully-working 90-day software included: "complete data miner - qc-miner - text miner" bound with book

Handbook of Statistical Analysis and Data Mining Applications

Download Handbook Of Statistical Analysis And Data Mining Applications Book or Ebook File with PDF Epub Audio and Full format File

Author by : Gary Miner
Languange Used : English, France, Spanish, Italia and chinese
Page : 864
Isbn : 9780124166325
Identifier : 0124166326
Release : 2017-07-01
Publisher by : Academic Press
Category : Computers
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Description : Read Now Handbook Of Statistical Analysis And Data Mining Applications by Gary Miner and you can download with pub, pdf, txt, doc, and more file format with free account. "the 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 the 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 industries, from science and engineering, to medicine, academia, and commerce. written 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 includes extensive case studies, examples, ms powerpoint slides and datasets, along with a cd-dvd with valuable fully working 90-day software 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

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

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Author by : Gary Miner
Languange Used : English, France, Spanish, Italia and chinese
Page : 1000
Isbn : 0123870119
Identifier : 9780123870117
Release : 2012-01-25
Publisher by : Academic Press
Category : Mathematics
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Description : Read Now Practical Text Mining And Statistical Analysis For Non Structured Text Data Applications by Gary Miner and you can download with pub, pdf, txt, doc, and more file format with free account. practical text mining and statistical analysis for non-structured text data applications brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. winner of a 2012 prose award in computing and information sciences from the association of american publishers, this book presents a comprehensive how-to reference that shows the user how to conduct text mining and statistically analyze results. in addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities. the world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. this makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. as the internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible numerous examples, tutorials, power points and datasets available via companion website on elsevierdirect.com glossary of text mining terms provided in the appendix

Data Mining and Data Visualization

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Author by : no defined
Languange Used : English, France, Spanish, Italia and chinese
Page : 800
Isbn : 9780080459400
Identifier : 0080459404
Release : 2005-05-02
Publisher by : Elsevier
Category : Mathematics
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Description : Read Now Data Mining And Data Visualization by no defined and you can download with pub, pdf, txt, doc, and more file format with free account. data mining and data visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. the book is divided into three sections. the first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files. the second section focuses on a variety of statistical methodologies that have proven to be effective in data mining applications. these include clustering, classification, multivariate density estimation, tree-based methods, pattern recognition, outlier detection, genetic algorithms, and dimensionality reduction. the third section focuses on data visualization and covers issues of visualization of high-dimensional data, novel graphical techniques with a focus on human factors, interactive graphics, and data visualization using virtual reality. this book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with a new data paradigm. distinguished contributors who are international experts in aspects of data mining includes data mining approaches to non-numerical data mining including text data, internet traffic data, and geographic data highly topical discussions reflecting current thinking on contemporary technical issues, e.g. streaming data discusses taxonomy of dataset sizes, computational complexity, and scalability usually ignored in most discussions thorough discussion of data visualization issues blending statistical, human factors, and computational insights

Applied Data Mining Statistical Methods for Business and Industry

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Author by : Paolo Giudici
Languange Used : English, France, Spanish, Italia and chinese
Page : 376
Isbn : 0470871393
Identifier : 9780470871393
Release : 2005-09-27
Publisher by : John Wiley & Sons
Category : Computers
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Description : Read Now Applied Data Mining by Paolo Giudici and you can download with pub, pdf, txt, doc, and more file format with free account. data mining can be defined as the process of selection, exploration and modelling of large databases, in order to discover models and patterns. the increasing availability of data in the current information society has led to the need for valid tools for its modelling and analysis. data mining and applied statistical methods are the appropriate tools to extract such knowledge from data. applications occur in many different fields, including statistics, computer science, machine learning, economics, marketing and finance. this book is the first to describe applied data mining methods in a consistent statistical framework, and then show how they can be applied in practice. all the methods described are either computational, or of a statistical modelling nature. complex probabilistic models and mathematical tools are not used, so the book is accessible to a wide audience of students and industry professionals. the second half of the book consists of nine case studies, taken from the author's own work in industry, that demonstrate how the methods described can be applied to real problems. provides a solid introduction to applied data mining methods in a consistent statistical framework includes coverage of classical, multivariate and bayesian statistical methodology includes many recent developments such as web mining, sequential bayesian analysis and memory based reasoning each statistical method described is illustrated with real life applications features a number of detailed case studies based on applied projects within industry incorporates discussion on software used in data mining, with particular emphasis on sas supported by a website featuring data sets, software and additional material includes an extensive bibliography and pointers to further reading within the text author has many years experience teaching introductory and multivariate statistics and data mining, and working on applied projects within industry a valuable resource for advanced undergraduate and graduate students of applied statistics, data mining, computer science and economics, as well as for professionals working in industry on projects involving large volumes of data - such as in marketing or financial risk management.

The Handbook of Data Mining

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Author by : Nong Ye
Languange Used : English, France, Spanish, Italia and chinese
Page : 720
Isbn : 1410607518
Identifier : 9781410607515
Release : 2003-04-01
Publisher by : CRC Press
Category : Computers
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Description : Read Now The Handbook Of Data Mining by Nong Ye and you can download with pub, pdf, txt, doc, and more file format with free account. created with the input of a distinguished international board of the foremost authorities in data mining from academia and industry, the handbook of data mining presents comprehensive coverage of data mining concepts and techniques. algorithms, methodologies, management issues, and tools are all illustrated through engaging examples and real-world applications to ease understanding of the materials. this book is organized into three parts. part i presents various data mining methodologies, concepts, and available software tools for each methodology. part ii addresses various issues typically faced in the management of data mining projects and tips on how to maximize outcome utility. part iii features numerous real-world applications of these techniques in a variety of areas, including human performance, geospatial, bioinformatics, on- and off-line customer transaction activity, security-related computer audits, network traffic, text and image, and manufacturing quality. this handbook is ideal for researchers and developers who want to use data mining techniques to derive scientific inferences where extensive data is available in scattered reports and publications. it is also an excellent resource for graduate-level courses on data mining and decision and expert systems methodology.

Ensemble Methods in Data Mining Improving Accuracy Through Combining Predictions

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Author by : Giovanni Seni
Languange Used : English, France, Spanish, Italia and chinese
Page : 108
Isbn : 1608452840
Identifier : 9781608452842
Release : 2010
Publisher by : Morgan & Claypool Publishers
Category : Computers
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Description : Read Now Ensemble Methods In Data Mining by Giovanni Seni and you can download with pub, pdf, txt, doc, and more file format with free account. "ensemble methods have been called the most influential development in data mining and machine learning in the past decade. they combine multiple models into one usually more accurate than the best of its components. ensembles can provide a critical boost to industrial challenges -- from investment timing to drug discovery, and fraud detection to recommendation systems -- where predictive accuracy is more vital than model interpretability. ensembles are useful with all modeling algorithms, but this book focuses on decision trees to explain them most clearly. after describing trees and their strengths and weaknesses, the authors provide an overview of regularization -- today understood to be a key reason for the superior performance of modern ensembling algorithms. the book continues with a clear description of two recent developments: importance sampling (is) and rule ensembles (re). is reveals classic ensemble methods -- bagging, random forests, and boosting -- to be special cases of a single algorithm, thereby showing how to improve their accuracy and speed. res are linear rule models derived from decision tree ensembles. they are the most interpretable version of ensembles, which is essential to applications such as credit scoring and fault diagnosis. lastly, the authors explain the paradox of how ensembles achieve greater accuracy on new data despite their (apparently much greater) complexity."--publisher's website.

Statistical and Machine-Learning Data Mining Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition

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Author by : Bruce Ratner
Languange Used : English, France, Spanish, Italia and chinese
Page : 542
Isbn : 1466551216
Identifier : 9781466551213
Release : 2012-02-28
Publisher by : CRC Press
Category : Business & Economics
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Description : Read Now Statistical And Machine Learning Data Mining by Bruce Ratner and you can download with pub, pdf, txt, doc, and more file format with free account. the second edition of a bestseller, statistical and machine-learning data mining: techniques for better predictive modeling and analysis of big data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. the first edition, titled statistical modeling and analysis for database marketing: effective techniques for mining big data, contained 17 chapters of innovative and practical statistical data mining techniques. in this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has completely revised, reorganized, and repositioned the original chapters and produced 14 new chapters of creative and useful machine-learning data mining techniques. in sum, the 31 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. the statistical data mining methods effectively consider big data for identifying structures (variables) with the appropriate predictive power in order to yield reliable and robust large-scale statistical models and analyses. in contrast, the author's own geniq model provides machine-learning solutions to common and virtually unapproachable statistical problems. geniq makes this possible — its utilitarian data mining features start where statistical data mining stops. this book contains essays offering detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. they address each methodology and assign its application to a specific type of problem. to better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. while this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.

Data Mining and Knowledge Discovery Handbook

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Author by : Oded Maimon
Languange Used : English, France, Spanish, Italia and chinese
Page : 1383
Isbn : 038725465X
Identifier : 9780387254654
Release : 2006-05-28
Publisher by : Springer Science & Business Media
Category : Computers
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Description : Read Now Data Mining And Knowledge Discovery Handbook by Oded Maimon and you can download with pub, pdf, txt, doc, and more file format with free account. data mining and knowledge discovery handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (dm) and knowledge discovery in databases (kdd) into a coherent and unified repository. this book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. this volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. data mining and knowledge discovery handbook is designed for research scientists and graduate-level students in computer science and engineering. this book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.

Data Mining and Statistics for Decision Making

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Author by : Stéphane Tufféry
Languange Used : English, France, Spanish, Italia and chinese
Page : 716
Isbn : 9780470979280
Identifier : 0470979283
Release : 2011-03-23
Publisher by : John Wiley & Sons
Category : Computers
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Description : Read Now Data Mining And Statistics For Decision Making by Stéphane Tufféry and you can download with pub, pdf, txt, doc, and more file format with free account. data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. this book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized linear models, regularized regression, pls regression, decision trees, neural networks, support vector machines, vapnik theory, naive bayesian classifier, ensemble learning and detection of association rules. they are discussed along with illustrative examples throughout the book to explain the theory of these methods, as well as their strengths and limitations. key features: presents a comprehensive introduction to all techniques used in data mining and statistical learning, from classical to latest techniques. starts from basic principles up to advanced concepts. includes many step-by-step examples with the main software (r, sas, ibm spss) as well as a thorough discussion and comparison of those software. gives practical tips for data mining implementation to solve real world problems. looks at a range of tools and applications, such as association rules, web mining and text mining, with a special focus on credit scoring. supported by an accompanying website hosting datasets and user analysis. statisticians and business intelligence analysts, students as well as computer science, biology, marketing and financial risk professionals in both commercial and government organizations across all business and industry sectors will benefit from this book.

Statistics, Data Mining, and Machine Learning in Astronomy A Practical Python Guide for the Analysis of Survey Data

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Author by : Željko Ivezić
Languange Used : English, France, Spanish, Italia and chinese
Page : 552
Isbn : 1400848911
Identifier : 9781400848911
Release : 2014-01-05
Publisher by : Princeton University Press
Category : Science
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Description : Read Now Statistics Data Mining And Machine Learning In Astronomy by Željko Ivezić and you can download with pub, pdf, txt, doc, and more file format with free account. as telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. this book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the panoramic survey telescope and rapid response system, the dark energy survey, and the upcoming large synoptic survey telescope. it serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. statistics, data mining, and machine learning in astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. for all applications described in the book, python code and example data sets are provided. the supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the sloan digital sky survey) and are easy to download and use. the accompanying python code is publicly available, well documented, and follows uniform coding standards. together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets features real-world data sets from contemporary astronomical surveys uses a freely available python codebase throughout ideal for students and working astronomers