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Causal Models and Intelligent Data Management

2012-12-06 Computers
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Release : 2012-12-06
Genre : Computers
Kind : eBook
Book Rating : 481/5 ( reviews)

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Book Synopsis Causal Models and Intelligent Data Management by : Alex Gammerman

Download or read book Causal Models and Intelligent Data Management written by Alex Gammerman. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: The need to electronically store, manipulate and analyze large-scale, high-dimensional data sets requires new computational methods. This book presents new intelligent data management methods and tools, including new results from the field of inference. Leading experts also map out future directions of intelligent data analysis. This book will be a valuable reference for researchers exploring the interdisciplinary area between statistics and computer science as well as for professionals applying advanced data analysis methods in industry.

Intelligent Data Mining

2005-08-24 Mathematics
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Release : 2005-08-24
Genre : Mathematics
Kind : eBook
Book Rating : 565/5 ( reviews)

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Book Synopsis Intelligent Data Mining by : Da Ruan

Download or read book Intelligent Data Mining written by Da Ruan. This book was released on 2005-08-24. Available in PDF, EPUB and Kindle. Book excerpt: "Intelligent Data Mining – Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book.

Intelligent Data Engineering and Automated Learning - IDEAL 2002

2003-08-02 Computers
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Release : 2003-08-02
Genre : Computers
Kind : eBook
Book Rating : 759/5 ( reviews)

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Book Synopsis Intelligent Data Engineering and Automated Learning - IDEAL 2002 by : Hujun Yin

Download or read book Intelligent Data Engineering and Automated Learning - IDEAL 2002 written by Hujun Yin. This book was released on 2003-08-02. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2002, held in Manchester, UK in August 2002. The 89 revised papers presented were carefully reviewed and selected from more than 150 submissions. The book offers topical sections on data mining, knowledge engineering, text and document processing, internet applications, agent technology, autonomous mining, financial engineering, bioinformatics, learning systems, and pattern recognition.

Data Mining: Foundations and Practice

2008-08-17 Technology & Engineering
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Release : 2008-08-17
Genre : Technology & Engineering
Kind : eBook
Book Rating : 888/5 ( reviews)

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Book Synopsis Data Mining: Foundations and Practice by : Tsau Young Lin

Download or read book Data Mining: Foundations and Practice written by Tsau Young Lin. This book was released on 2008-08-17. Available in PDF, EPUB and Kindle. Book excerpt: The IEEE ICDM 2004 workshop on the Foundation of Data Mining and the IEEE ICDM 2005 workshop on the Foundation of Semantic Oriented Data and Web Mining focused on topics ranging from the foundations of data mining to new data mining paradigms. The workshops brought together both data mining researchers and practitioners to discuss these two topics while seeking solutions to long standing data mining problems and stimul- ing new data mining research directions. We feel that the papers presented at these workshops may encourage the study of data mining as a scienti?c ?eld and spark new communications and collaborations between researchers and practitioners. Toexpressthevisionsforgedintheworkshopstoawiderangeofdatam- ing researchers and practitioners and foster active participation in the study of foundations of data mining, we edited this volume by involving extended and updated versions of selected papers presented at those workshops as well as some other relevant contributions. The content of this book includes st- ies of foundations of data mining from theoretical, practical, algorithmical, and managerial perspectives. The following is a brief summary of the papers contained in this book.

Causal Inference in Statistics

2016-01-25 Mathematics
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Release : 2016-01-25
Genre : Mathematics
Kind : eBook
Book Rating : 862/5 ( reviews)

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Book Synopsis Causal Inference in Statistics by : Judea Pearl

Download or read book Causal Inference in Statistics written by Judea Pearl. This book was released on 2016-01-25. Available in PDF, EPUB and Kindle. Book excerpt: CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.

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