Multiple Instance Learning PDF
By:Francisco Herrera,Sebastián Ventura,Rafael Bello,Chris Cornelis,Amelia Zafra,Dánel Sánchez-Tarragó,Sarah Vluymans
Published on 2016-11-08 by Springer
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This book provides a general overview of multiple instance learning (MIL), defining the framework and covering the central paradigms. The authors discuss the most important algorithms for MIL such as classification, regression and clustering. With a focus on classification, a taxonomy is set and the most relevant proposals are specified. Efficient algorithms are developed to discover relevant information when working with uncertainty. Key representative applications are included. This book carries out a study of the key related fields of distance metrics and alternative hypothesis. Chapters examine new and developing aspects of MIL such as data reduction for multi-instance problems and imbalanced MIL data. Class imbalance for multi-instance problems is defined at the bag level, a type of representation that utilizes ambiguity due to the fact that bag labels are available, but the labels of the individual instances are not defined. Additionally, multiple instance multiple label learning is explored. This learning framework introduces flexibility and ambiguity in the object representation providing a natural formulation for representing complicated objects. Thus, an object is represented by a bag of instances and is allowed to have associated multiple class labels simultaneously. This book is suitable for developers and engineers working to apply MIL techniques to solve a variety of real-world problems. It is also useful for researchers or students seeking a thorough overview of MIL literature, methods, and tools.
This Book was ranked at 32 by Google Books for keyword medical computer applications acl.
Book ID of Multiple Instance Learning's Books is 5NZ2DQAAQBAJ, Book which was written byFrancisco Herrera,Sebastián Ventura,Rafael Bello,Chris Cornelis,Amelia Zafra,Dánel Sánchez-Tarragó,Sarah Vluymanshave ETAG "yD5CeLnvy3k"
Book which was published by Springer since 2016-11-08 have ISBNs, ISBN 13 Code is 9783319477596 and ISBN 10 Code is 3319477595
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Book which have "233 Pages" is Printed at BOOK under CategoryComputers
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