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Author: James Bradley
Publisher: SAGE
ISBN: 0761909222
Category : Social Science
Languages : en
Pages : 225
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Book Description
Undeniably, the amount of "information" in our culture has increased by leaps and bounds. At the same time, discussion of values, norms and purpose is often missing from the discourse of social research - especially by those who work within the positivist framework. The authors of this book develop principles to guide the use of data and models in the human sciences. Writing as scholars who are at home with empirical and mathematical social science, yet taking seriously the critiques of this heritage, they propose ways of developing norms without becoming subjective.
Author: James Bradley
Publisher: SAGE
ISBN: 0761909222
Category : Social Science
Languages : en
Pages : 225
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Book Description
Undeniably, the amount of "information" in our culture has increased by leaps and bounds. At the same time, discussion of values, norms and purpose is often missing from the discourse of social research - especially by those who work within the positivist framework. The authors of this book develop principles to guide the use of data and models in the human sciences. Writing as scholars who are at home with empirical and mathematical social science, yet taking seriously the critiques of this heritage, they propose ways of developing norms without becoming subjective.
Author: Gary Smith
Publisher: Abrams
ISBN: 1468310682
Category : Social Science
Languages : en
Pages : 192
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Book Description
How statistical data is used, misused, and abused every day to fool us: “A very entertaining book about a very serious problem.” —Robert J. Shiller, winner of the Nobel Prize in Economics and author of Irrational Exuberance Did you know that baseball players whose names begin with “D” are more likely to die young? That Asian Americans are most susceptible to heart attacks on the fourth day of the month? That drinking a full pot of coffee every morning adds years to your life, but one cup a day increases your pancreatic cancer risk? These “facts” have been argued with a straight face by credentialed researchers and backed up with reams of data and convincing statistics. As Nobel Prize–winning economist Ronald Coase cynically observed, “If you torture data long enough, it will confess.” Lying with statistics is a time-honored con. In Standard Deviations, economics professor Gary Smith walks us through the various tricks and traps that people use to back up their own crackpot theories. Sometimes, the unscrupulous deliberately try to mislead us. Other times, the well-intentioned are blissfully unaware of the mischief they are committing. Today, data is so plentiful that researchers spend precious little time distinguishing between good, meaningful indicators and total rubbish. Not only do others use data to fool us, we fool ourselves. Drawing on breakthrough research in behavioral economics and using clear examples, Standard Deviations demystifies the science behind statistics and makes it easy to spot the fraud all around us. “An entertaining primer . . . packed with figures, tables, graphs and ludicrous examples from people who know better (academics, scientists) and those who don’t (political candidates, advertisers).” —Kirkus Reviews (starred review)
Author: Neeraj Bhargava
Publisher: John Wiley & Sons
ISBN: 1119760402
Category : Technology & Engineering
Languages : en
Pages : 322
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Book Description
ARTIFICIAL INTELLIGENCE AND DATA MINING IN SECURITY FRAMEWORKS Written and edited by a team of experts in the field, this outstanding new volume offers solutions to the problems of security, outlining the concepts behind allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to artificial intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalized security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and data mining and several other computing technologies to deploy such a system in an effective manner. This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice. This groundbreaking new volume presents these topics and trends, bridging the research gap on AI and data mining to enable wide-scale implementation. Whether for the veteran engineer or the student, this is a must-have for any library. This groundbreaking new volume: Clarifies the understanding of certain key mechanisms of technology helpful in the use of artificial intelligence and data mining in security frameworks Covers practical approaches to the problems engineers face in working in this field, focusing on the applications used every day Contains numerous examples, offering critical solutions to engineers and scientists Presents these new applications of AI and data mining that are of prime importance to human civilization as a whole
Author:
Publisher:
ISBN:
Category : Medicine
Languages : en
Pages : 2164
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Book Description
Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.
Author: Kathleen Ann Johnson
Publisher:
ISBN:
Category : Ambulatory medical care
Languages : en
Pages : 678
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Book Description
Author: Sugumaran, Vijayan
Publisher: IGI Global
ISBN: 1599049422
Category : Computers
Languages : en
Pages : 2469
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Book Description
This set compiles more than 240 chapters from the world's leading experts to provide a foundational body of research to drive further evolution and innovation of these next-generation technologies and their applications, of which scientific, technological, and commercial communities have only begun to scratch the surface.
Author:
Publisher:
ISBN:
Category : Drug abuse
Languages : en
Pages : 558
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Book Description
Author: Grant Fleming
Publisher: John Wiley & Sons
ISBN: 1119741777
Category : Computers
Languages : en
Pages : 304
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Book Description
Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of “Black box” algorithms that are difficult or impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box models Diagnose bias and unfairness within models using multiple metrics Audit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.
Author: William J. Tastle
Publisher: Springer Science & Business Media
ISBN: 1461442230
Category : Computers
Languages : en
Pages : 279
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Book Description
This volume directly addresses the complexities involved in data mining and the development of new algorithms, built on an underlying theory consisting of linear and non-linear dynamics, data selection, filtering, and analysis, while including analytical projection and prediction. The results derived from the analysis are then further manipulated such that a visual representation is derived with an accompanying analysis. The book brings very current methods of analysis to the forefront of the discipline, provides researchers and practitioners the mathematical underpinning of the algorithms, and the non-specialist with a visual representation such that a valid understanding of the meaning of the adaptive system can be attained with careful attention to the visual representation. The book presents, as a collection of documents, sophisticated and meaningful methods that can be immediately understood and applied to various other disciplines of research. The content is composed of chapters addressing: An application of adaptive systems methodology in the field of post-radiation treatment involving brain volume differences in children; A new adaptive system for computer-aided diagnosis of the characterization of lung nodules; A new method of multi-dimensional scaling with minimal loss of information; A description of the semantics of point spaces with an application on the analysis of terrorist attacks in Afghanistan; The description of a new family of meta-classifiers; A new method of optimal informational sorting; A general method for the unsupervised adaptive classification for learning; and the presentation of two new theories, one in target diffusion and the other in twisting theory.
Author:
Publisher:
ISBN:
Category : Alcoholism
Languages : en
Pages : 698
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Book Description
