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Robust Data Mining Techniques with Application in Biomedicine and Engineering

2011
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Release : 2011
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Kind : eBook
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Book Synopsis Robust Data Mining Techniques with Application in Biomedicine and Engineering by : Petros Xanthopoulos

Download or read book Robust Data Mining Techniques with Application in Biomedicine and Engineering written by Petros Xanthopoulos. This book was released on 2011. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: Analysis and interpretation of large datasets is a very significant problem that arises in many areas of science. The task of data analysis becomes even harder when data are uncertain or imprecise. Such uncertainties introduce bias and make massive data analysis an even more challenging task. Over the years there have been developed many mathematical methodologies for data analysis based on mathematical programming. In this field, the deterministic approach for handling uncertainty and immunizing algorithms against undesired scenarios is robust optimization. In this work we examine the application of robust optimization is some well known data mining algorithms. We explore the optimization structure of such algorithms and then we state their robust counterpart formulation.

Robust Data Mining

2012-11-28 Mathematics
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Release : 2012-11-28
Genre : Mathematics
Kind : eBook
Book Rating : 780/5 ( reviews)

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Book Synopsis Robust Data Mining by : Petros Xanthopoulos

Download or read book Robust Data Mining written by Petros Xanthopoulos. This book was released on 2012-11-28. Available in PDF, EPUB and Kindle. Book excerpt: Data uncertainty is a concept closely related with most real life applications that involve data collection and interpretation. Examples can be found in data acquired with biomedical instruments or other experimental techniques. Integration of robust optimization in the existing data mining techniques aim to create new algorithms resilient to error and noise. This work encapsulates all the latest applications of robust optimization in data mining. This brief contains an overview of the rapidly growing field of robust data mining research field and presents the most well known machine learning algorithms, their robust counterpart formulations and algorithms for attacking these problems. This brief will appeal to theoreticians and data miners working in this field.

Data Mining in Biomedical Imaging, Signaling, and Systems

2016-04-19 Computers
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Release : 2016-04-19
Genre : Computers
Kind : eBook
Book Rating : 395/5 ( reviews)

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Book Synopsis Data Mining in Biomedical Imaging, Signaling, and Systems by : Sumeet Dua

Download or read book Data Mining in Biomedical Imaging, Signaling, and Systems written by Sumeet Dua. This book was released on 2016-04-19. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive volume demonstrates the broad scope of uses for data mining and includes detailed strategies and methodologies for analyzing data from biomedical images, signals, and systems. Written by experts in the field, it presents data mining techniques in the context of various important clinical issues, including diagnosis and grading of depression, identification and classification of arrhythmia and ischemia, and description of classification paradigms for mammograms. The book provides ample information and techniques to benefit researchers, practitioners, and educators of biomedical science and engineering.

Data Mining Applications in Engineering and Medicine

2012-08-29 Computers
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Release : 2012-08-29
Genre : Computers
Kind : eBook
Book Rating : 208/5 ( reviews)

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Book Synopsis Data Mining Applications in Engineering and Medicine by : Adem Karahoca

Download or read book Data Mining Applications in Engineering and Medicine written by Adem Karahoca. This book was released on 2012-08-29. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining Applications in Engineering and Medicine targets to help data miners who wish to apply different data mining techniques. Data mining generally covers areas of statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, etc. In this book, most of the areas are covered by describing different applications. This is why you will find here why and how Data Mining can also be applied to the improvement of project management. Since Data Mining has been widely used in a medical field, this book contains different chapters reffering to some aspects and importance of its use in the mentioned field: Incorporating Domain Knowledge into Medical Image Mining, Data Mining Techniques in Pharmacovigilance, Electronic Documentation of Clinical Pharmacy Interventions in Hospitals etc. We hope that this book will inspire readers to pursue education and research in this emerging field.

Data Mining for Scientific and Engineering Applications

2013-12-01 Computers
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Release : 2013-12-01
Genre : Computers
Kind : eBook
Book Rating : 338/5 ( reviews)

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Book Synopsis Data Mining for Scientific and Engineering Applications by : R.L. Grossman

Download or read book Data Mining for Scientific and Engineering Applications written by R.L. Grossman. This book was released on 2013-12-01. Available in PDF, EPUB and Kindle. Book excerpt: Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

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