Kernel Based Data Fusion For Machine Learning
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Kernel Based Data Fusion For Machine Learning
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Author : Shi Yu
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-26
Kernel Based Data Fusion For Machine Learning written by Shi Yu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-26 with Computers categories.
Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines. In the first part, this book begins with a brief survey of additive models and Rayleigh quotient objectives in machine learning, and then introduces kernel fusion as the additive expansion of support vector machines in the dual problem. The second part presents several novel kernel fusion algorithms and some real applications in supervised and unsupervised learning. The last part of the book substantiates the value of the proposed theories and algorithms in MerKator, an open software to identify disease relevant genes based on the integration of heterogeneous genomic data sources in multiple species. The topics presented in this book are meant for researchers or students who use support vector machines. Several topics addressed in the book may also be interesting to computational biologists who want to tackle data fusion challenges in real applications. The background required of the reader is a good knowledge of data mining, machine learning and linear algebra.
Kernel Based Data Fusion For Machine Learning
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Author : Shi Yu
language : en
Publisher: Springer
Release Date : 2011-03-29
Kernel Based Data Fusion For Machine Learning written by Shi Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-29 with Computers categories.
Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines. In the first part, this book begins with a brief survey of additive models and Rayleigh quotient objectives in machine learning, and then introduces kernel fusion as the additive expansion of support vector machines in the dual problem. The second part presents several novel kernel fusion algorithms and some real applications in supervised and unsupervised learning. The last part of the book substantiates the value of the proposed theories and algorithms in MerKator, an open software to identify disease relevant genes based on the integration of heterogeneous genomic data sources in multiple species. The topics presented in this book are meant for researchers or students who use support vector machines. Several topics addressed in the book may also be interesting to computational biologists who want to tackle data fusion challenges in real applications. The background required of the reader is a good knowledge of data mining, machine learning and linear algebra.
Machine Learning
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Author : Hamed Farhadi
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-09-19
Machine Learning written by Hamed Farhadi and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-19 with Computers categories.
The volume of data that is generated, stored, and communicated across different industrial sections, business units, and scientific research communities has been rapidly expanding. The recent developments in cellular telecommunications and distributed/parallel computation technology have enabled real-time collection and processing of the generated data across different sections. On the one hand, the internet of things (IoT) enabled by cellular telecommunication industry connects various types of sensors that can collect heterogeneous data. On the other hand, the recent advances in computational capabilities such as parallel processing in graphical processing units (GPUs) and distributed processing over cloud computing clusters enabled the processing of a vast amount of data. There has been a vital need to discover important patterns and infer trends from a large volume of data (so-called Big Data) to empower data-driven decision-making processes. Tools and techniques have been developed in machine learning to draw insightful conclusions from available data in a structured and automated fashion. Machine learning algorithms are based on concepts and tools developed in several fields including statistics, artificial intelligence, information theory, cognitive science, and control theory. The recent advances in machine learning have had a broad range of applications in different scientific disciplines. This book covers recent advances of machine learning techniques in a broad range of applications in smart cities, automated industry, and emerging businesses.
Machine Learning
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Author : Andrea Mechelli
language : en
Publisher: Academic Press
Release Date : 2019-11-14
Machine Learning written by Andrea Mechelli and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-14 with Medical categories.
Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians are using machine learning methods to develop and validate tools for assisting the diagnosis and treatment of patients with brain disorders. Machine Learning: Methods and Applications to Brain Disorders provides an up-to-date overview of how these methods can be applied to brain disorders, including both psychiatric and neurological disease. This book is written for a non-technical audience, such as neuroscientists, psychologists, psychiatrists, neurologists and health care practitioners. - Provides a non-technical introduction to machine learning and applications to brain disorders - Includes a detailed description of the most commonly used machine learning algorithms as well as some novel and promising approaches - Covers the main methodological challenges in the application of machine learning to brain disorders - Provides a step-by-step tutorial for implementing a machine learning pipeline to neuroimaging data in Python
Analyzing Network Data In Biology And Medicine
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Author : Nataša Pržulj
language : en
Publisher: Cambridge University Press
Release Date : 2019-03-28
Analyzing Network Data In Biology And Medicine written by Nataša Pržulj and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-28 with Language Arts & Disciplines categories.
Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.
Pattern Recognition And Machine Intelligence
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Author : B. Uma Shankar
language : en
Publisher: Springer
Release Date : 2017-11-22
Pattern Recognition And Machine Intelligence written by B. Uma Shankar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-22 with Computers categories.
This book constitutes the proceedings of the 7th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2017,held in Kolkata, India, in December 2017. The total of 86 full papers presented in this volume were carefully reviewed and selected from 293 submissions. They were organized in topical sections named: pattern recognition and machine learning; signal and image processing; computer vision and video processing; soft and natural computing; speech and natural language processing; bioinformatics and computational biology; data mining and big data analytics; deep learning; spatial data science and engineering; and applications of pattern recognition and machine intelligence.
Springer Handbook Of Computational Intelligence
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Author : Janusz Kacprzyk
language : en
Publisher: Springer
Release Date : 2015-05-28
Springer Handbook Of Computational Intelligence written by Janusz Kacprzyk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-28 with Technology & Engineering categories.
The Springer Handbook for Computational Intelligence is the first book covering the basics, the state-of-the-art and important applications of the dynamic and rapidly expanding discipline of computational intelligence. This comprehensive handbook makes readers familiar with a broad spectrum of approaches to solve various problems in science and technology. Possible approaches include, for example, those being inspired by biology, living organisms and animate systems. Content is organized in seven parts: foundations; fuzzy logic; rough sets; evolutionary computation; neural networks; swarm intelligence and hybrid computational intelligence systems. Each Part is supervised by its own Part Editor(s) so that high-quality content as well as completeness are assured.
Combinatorial Machine Learning
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Author : Mikhail Moshkov
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-29
Combinatorial Machine Learning written by Mikhail Moshkov and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-29 with Computers categories.
Decision trees and decision rule systems are widely used in different applications as algorithms for problem solving, as predictors, and as a way for knowledge representation. Reducts play key role in the problem of attribute (feature) selection. The aims of this book are (i) the consideration of the sets of decision trees, rules and reducts; (ii) study of relationships among these objects; (iii) design of algorithms for construction of trees, rules and reducts; and (iv) obtaining bounds on their complexity. Applications for supervised machine learning, discrete optimization, analysis of acyclic programs, fault diagnosis, and pattern recognition are considered also. This is a mixture of research monograph and lecture notes. It contains many unpublished results. However, proofs are carefully selected to be understandable for students. The results considered in this book can be useful for researchers in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory and logical analysis of data. The book can be used in the creation of courses for graduate students.
Braverman Readings In Machine Learning Key Ideas From Inception To Current State
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Author : Lev Rozonoer
language : en
Publisher: Springer
Release Date : 2018-08-30
Braverman Readings In Machine Learning Key Ideas From Inception To Current State written by Lev Rozonoer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-30 with Computers categories.
This state-of-the-art survey is dedicated to the memory of Emmanuil Markovich Braverman (1931-1977), a pioneer in developing machine learning theory. The 12 revised full papers and 4 short papers included in this volume were presented at the conference "Braverman Readings in Machine Learning: Key Ideas from Inception to Current State" held in Boston, MA, USA, in April 2017, commemorating the 40th anniversary of Emmanuil Braverman's decease. The papers present an overview of some of Braverman's ideas and approaches. The collection is divided in three parts. The first part bridges the past and the present and covers the concept of kernel function and its application to signal and image analysis as well as clustering. The second part presents a set of extensions of Braverman's work to issues of current interest both in theory and applications of machine learning. The third part includes short essays by a friend, a student, and a colleague.
Medical Informatics
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Author : Hsinchun Chen
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-07-19
Medical Informatics written by Hsinchun Chen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-19 with Medical categories.
Knowledge Management and Data Mining in Biomedicine covers the basic foundations of the area while extending the foundational material to include the recent leading-edge research in the field. The newer concepts, techniques, and practices of biomedical knowledge management and data mining are introduced and examined in detail. It is the research and applications in these areas that are raising the technical horizons and expanding the utility of informatics to an increasing number of biomedical professionals and researchers. These concepts and techniques are illustrated with detailed case studies.