Learning To Classify Text Using Support Vector Machines
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Learning To Classify Text Using Support Vector Machines
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Author : Thorsten Joachims
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Learning To Classify Text Using Support Vector Machines written by Thorsten Joachims 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 2012-12-06 with Computers categories.
Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes with a learning theory that can guide real-world applications. Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a statistical learning model of text classification. In addition, it includes an overview of the field of text classification, making it self-contained even for newcomers to the field. This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning.
Learning To Classify Text Using Support Vector Machines
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Author : Thorsten Joachims
language : en
Publisher:
Release Date : 2002
Learning To Classify Text Using Support Vector Machines written by Thorsten Joachims and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
Imbalanced Learning
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Author : Haibo He
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-07
Imbalanced Learning written by Haibo He and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-07 with Technology & Engineering categories.
The first book of its kind to review the current status andfuture direction of the exciting new branch of machinelearning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system canlearn when it is provided with imbalanced data. Solving imbalancedlearning problems is critical in numerous data-intensive networkedsystems, including surveillance, security, Internet, finance,biomedical, defense, and more. Due to the inherent complexcharacteristics of imbalanced data sets, learning from such datarequires new understandings, principles, algorithms, and tools totransform vast amounts of raw data efficiently into information andknowledge representation. The first comprehensive look at this new branch of machinelearning, this book offers a critical review of the problem ofimbalanced learning, covering the state of the art in techniques,principles, and real-world applications. Featuring contributionsfrom experts in both academia and industry, Imbalanced Learning:Foundations, Algorithms, and Applications provides chaptercoverage on: Foundations of Imbalanced Learning Imbalanced Datasets: From Sampling to Classifiers Ensemble Methods for Class Imbalance Learning Class Imbalance Learning Methods for Support VectorMachines Class Imbalance and Active Learning Nonstationary Stream Data Learning with Imbalanced ClassDistribution Assessment Metrics for Imbalanced Learning Imbalanced Learning: Foundations, Algorithms, andApplications will help scientists and engineers learn how totackle the problem of learning from imbalanced datasets, and gaininsight into current developments in the field as well as futureresearch directions.
Rule Extraction From Support Vector Machines
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Author : Joachim Diederich
language : en
Publisher: Springer
Release Date : 2007-12-27
Rule Extraction From Support Vector Machines written by Joachim Diederich and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-27 with Technology & Engineering categories.
Support vector machines (SVMs) are one of the most active research areas in machine learning. SVMs have shown good performance in a number of applications, including text and image classification. However, the learning capability of SVMs comes at a cost – an inherent inability to explain in a comprehensible form, the process by which a learning result was reached. Hence, the situation is similar to neural networks, where the apparent lack of an explanation capability has led to various approaches aiming at extracting symbolic rules from neural networks. For SVMs to gain a wider degree of acceptance in fields such as medical diagnosis and security sensitive areas, it is desirable to offer an explanation capability. User explanation is often a legal requirement, because it is necessary to explain how a decision was reached or why it was made. This book provides an overview of the field and introduces a number of different approaches to extracting rules from support vector machines developed by key researchers. In addition, successful applications are outlined and future research opportunities are discussed. The book is an important reference for researchers and graduate students, and since it provides an introduction to the topic, it will be important in the classroom as well. Because of the significance of both SVMs and user explanation, the book is of relevance to data mining practitioners and data analysts.
Mining Text Data
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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-03
Mining Text Data written by Charu C. Aggarwal 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 2012-02-03 with Computers categories.
Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.
Content Addressable Memories
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Author : Teuvo Kohonen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Content Addressable Memories written by Teuvo Kohonen 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 2012-12-06 with Computers categories.
Due to continual progress in the large-scale integration of semiconductor circuits, parallel computing principles can already be met in low-cost sys tems: numerous examples exist in image processing, for which special hard ware is implementable with quite modest resources even by nonprofessional designers. Principles of content addressing, if thoroughly understood, can thereby be applied effectively using standard components. On the other hand, mass storage based on associative principles still exists only in the long term plans of computer technologists. This situation is somewhat confused by the fact that certain expectations are held for the development of new storage media such as optical memories and "spin glasses" (metal alloys with low-density magnetic impurities). Their technologies, however, may not ripen until after "fifth generation" computers have been built. It seems that software methods for content addressing, especially those based on hash coding principles, are still holding their position firmly, and a few innovations have been developed recently. As they need no special hardware, one might expect that they will spread to a wide circle of users. This monograph is based on an extensive literature survey, most of which was published in the First Edition. I have added Chap. ?, which contains a review of more recent work. This updated book now has references to over 1200 original publications. In the editing of the new material, I received valuable help from Anneli HeimbUrger, M. Sc. , and Mrs. Leila Koivisto.
How To Fine Tune Support Vector Machines For Classification
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Author : Ionut B. Brandusoiu
language : en
Publisher: GAER Publishing House
Release Date : 2020-08-19
How To Fine Tune Support Vector Machines For Classification written by Ionut B. Brandusoiu and has been published by GAER Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-19 with Computers categories.
This book covers in the first part the theoretical aspects of support vector machines and their functionality, and then based on the discussed concepts it explains how to find-tune a support vector machine to yield highly accurate prediction results which are adaptable to any classification tasks. The introductory part is extremely beneficial to someone new to learning support vector machines, while the more advanced notions are useful for everyone who wants to understand the mathematics behind support vector machines and how to find-tune them in order to generate the best predictive performance of a certain classification model.
Pattern Classification
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Author : Shigeo Abe
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Pattern Classification written by Shigeo Abe 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 2012-12-06 with Computers categories.
This book provides a unified approach for developing a fuzzy classifier and explains the advantages and disadvantages of different classifiers through extensive performance evaluation of real data sets. It thus offers new learning paradigms for analyzing neural networks and fuzzy systems, while training fuzzy classifiers. Function approximation is also treated and function approximators are compared.
Computer And Computing Technologies In Agriculture
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Author : Daoliang Li
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-01-12
Computer And Computing Technologies In Agriculture written by Daoliang Li 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 2012-01-12 with Computers categories.
The three-volume set IFIP AICT 368-370 constitutes the refereed post-conference proceedings of the 5th IFIP TC 5, SIG 5.1 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2011, held in Beijing, China, in October 2011. The 189 revised papers presented were carefully selected from numerous submissions. They cover a wide range of interesting theories and applications of information technology in agriculture, including simulation models and decision-support systems for agricultural production, agricultural product quality testing, traceability and e-commerce technology, the application of information and communication technology in agriculture, and universal information service technology and service systems development in rural areas. The 62 papers included in the first volume focus on decision support systems, intelligent systems, and artificial intelligence applications.
Twin Support Vector Machines
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Author : Jayadeva
language : en
Publisher: Springer
Release Date : 2016-10-12
Twin Support Vector Machines written by Jayadeva and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-12 with Technology & Engineering categories.
This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments for classification and regression. In addition to presenting most of the basic models of TWSVM and twin support vector regression (TWSVR) available in the literature, it also discusses the important and challenging applications of this new machine learning methodology. A chapter on “Additional Topics” has been included to discuss kernel optimization and support tensor machine topics, which are comparatively new but have great potential in applications. It is primarily written for graduate students and researchers in the area of machine learning and related topics in computer science, mathematics, electrical engineering, management science and finance.