Rule Extraction From Support Vector Machine
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Rule Extraction From Support Vector Machines
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Author : Joachim Diederich
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-04
Rule Extraction From Support Vector Machines written by Joachim Diederich 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 2008-01-04 with Mathematics 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.
Rule Extraction From Support Vector Machine
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Author : Mohammed Farquad
language : en
Publisher: GRIN Verlag
Release Date : 2012-05-14
Rule Extraction From Support Vector Machine written by Mohammed Farquad and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-14 with Computers categories.
Doctoral Thesis / Dissertation from the year 2010 in the subject Computer Science - Applied, grade: none, course: Department of Computers and Information Sciences - Ph.D., language: English, abstract: Although Support Vector Machines have been used to develop highly accurate classification and regression models in various real-world problem domains, the most significant barrier is that SVM generates black box model that is difficult to understand. The procedure to convert these opaque models into transparent models is called rule extraction. This thesis investigates the task of extracting comprehensible models from trained SVMs, thereby alleviating this limitation. The primary contribution of the thesis is the proposal of various algorithms to overcome the significant limitations of SVM by taking a novel approach to the task of extracting comprehensible models. The basic contribution of the thesis are systematic review of literature on rule extraction from SVM, identifying gaps in the literature and proposing novel approaches for addressing the gaps. The contributions are grouped under three classes, decompositional, pedagogical and eclectic/hybrid approaches. Decompositional approach is closely intertwined with the internal workings of the SVM. Pedagogical approach uses SVM as an oracle to re-label training examples as well as artificially generated examples. In the eclectic/hybrid approach, a combination of these two methods is adopted. The thesis addresses various problems from the finance domain such as bankruptcy prediction in banks/firms, churn prediction in analytical CRM and Insurance fraud detection. Apart from this various benchmark datasets such as iris, wine and WBC for classification problems and auto MPG, body fat, Boston housing, forest fires and pollution for regression problems are also tested using the proposed appraoch. In addition, rule extraction from unbalanced datasets as well as from active learning based approaches has been explored. For
Rule Extraction From Support Vector Machine
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Author : Mohammed Farquad
language : en
Publisher: GRIN Verlag
Release Date : 2012-05-10
Rule Extraction From Support Vector Machine written by Mohammed Farquad and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-10 with Computers categories.
Doctoral Thesis / Dissertation from the year 2010 in the subject Computer Science - Applied, grade: none, , course: Department of Computers and Information Sciences - Ph.D., language: English, abstract: Although Support Vector Machines have been used to develop highly accurate classification and regression models in various real-world problem domains, the most significant barrier is that SVM generates black box model that is difficult to understand. The procedure to convert these opaque models into transparent models is called rule extraction. This thesis investigates the task of extracting comprehensible models from trained SVMs, thereby alleviating this limitation. The primary contribution of the thesis is the proposal of various algorithms to overcome the significant limitations of SVM by taking a novel approach to the task of extracting comprehensible models. The basic contribution of the thesis are systematic review of literature on rule extraction from SVM, identifying gaps in the literature and proposing novel approaches for addressing the gaps. The contributions are grouped under three classes, decompositional, pedagogical and eclectic/hybrid approaches. Decompositional approach is closely intertwined with the internal workings of the SVM. Pedagogical approach uses SVM as an oracle to re-label training examples as well as artificially generated examples. In the eclectic/hybrid approach, a combination of these two methods is adopted. The thesis addresses various problems from the finance domain such as bankruptcy prediction in banks/firms, churn prediction in analytical CRM and Insurance fraud detection. Apart from this various benchmark datasets such as iris, wine and WBC for classification problems and auto MPG, body fat, Boston housing, forest fires and pollution for regression problems are also tested using the proposed appraoch. In addition, rule extraction from unbalanced datasets as well as from active learning based approaches has been explored. For classification problems, various rule extraction methods such as FRBS, DT, ANFIS, CART and NBTree have been utilized. Additionally for regression problems, rule extraction methods such as ANFIS, DENFIS and CART have also been employed. Results are analyzed using accuracy, sensitivity, specificity, fidelity, AUC and t-test measures. Proposed approaches demonstrate their viability in extracting accurate, effective and comprehensible rule sets in various benchmark and real world problem domains across classification and regression problems. Future directions have been indicated to extend the approaches to newer variations of SVM as well as to other problem domains.
Rough Sets Fuzzy Sets Data Mining And Granular Computing
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Author : Hiroshi Sakai
language : en
Publisher: Springer
Release Date : 2009-12-15
Rough Sets Fuzzy Sets Data Mining And Granular Computing written by Hiroshi Sakai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-15 with Computers categories.
This book constitutes the refereed proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2009, held in Delhi, India in December 2009 in conjunction with the Third International Conference on Pattern Recognition and Machine Intelligence, PReMI 2009. RSFDGrC 2009 is the core component of a broader Rough Set Year in India initiative, RSIndia09. The 56 revised full papers presented together with 6 invited papers and a report on the Rough Set Year in India 2009 project were carefully reviewed and selected from a total of 130 submissions. The papers are organized in topical sections on foundations of rough sets and beyond; rought set algorithms and applications; fuzzy set foundations and applications; data mining and knowledge discovery; clustering and current trends in computing; and information retrieval and text mining.
Support Vector Machines And Evolutionary Algorithms For Classification
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Author : Catalin Stoean
language : en
Publisher: Springer
Release Date : 2014-05-15
Support Vector Machines And Evolutionary Algorithms For Classification written by Catalin Stoean and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-15 with Technology & Engineering categories.
When discussing classification, support vector machines are known to be a capable and efficient technique to learn and predict with high accuracy within a quick time frame. Yet, their black box means to do so make the practical users quite circumspect about relying on it, without much understanding of the how and why of its predictions. The question raised in this book is how can this ‘masked hero’ be made more comprehensible and friendly to the public: provide a surrogate model for its hidden optimization engine, replace the method completely or appoint a more friendly approach to tag along and offer the much desired explanations? Evolutionary algorithms can do all these and this book presents such possibilities of achieving high accuracy, comprehensibility, reasonable runtime as well as unconstrained performance.
Advanced Machine Learning Technologies And Applications
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2014-11-04
Advanced Machine Learning Technologies And Applications written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-04 with Computers categories.
This book constitutes the refereed proceedings of the Second International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2014, held in Cairo, Egypt, in November 2014. The 49 full papers presented were carefully reviewed and selected from 101 initial submissions. The papers are organized in topical sections on machine learning in Arabic text recognition and assistive technology; recommendation systems for cloud services; machine learning in watermarking/authentication and virtual machines; features extraction and classification; rough/fuzzy sets and applications; fuzzy multi-criteria decision making; Web-based application and case-based reasoning construction; social networks and big data sets.
Knowledge Based And Intelligent Information And Engineering Systems
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Author : Rossitza Setchi
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-08-30
Knowledge Based And Intelligent Information And Engineering Systems written by Rossitza Setchi 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 2010-08-30 with Computers categories.
The four-volume set LNAI 6276--6279 constitutes the refereed proceedings of the 14th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2010, held in Cardiff, UK, in September 2010. The 272 revised papers presented were carefully reviewed and selected from 360 submissions. They present the results of high-quality research on a broad range of intelligent systems topics.
Data Warehousing And Mining Concepts Methodologies Tools And Applications
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Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2008-05-31
Data Warehousing And Mining Concepts Methodologies Tools And Applications written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-31 with Technology & Engineering categories.
In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.
Computational Methods In Neural Modeling
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Author : José Mira
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-05-22
Computational Methods In Neural Modeling written by José Mira 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 2003-05-22 with Computers categories.
The two-volume set LNCS 2686 and LNCS 2687 constitute the refereed proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003, held in Maó, Menorca, Spain in June 2003. The 197 revised papers presented were carefully reviewed and selected for inclusion in the book and address the following topics: mathematical and computational methods in neural modelling, neurophysiological data analysis and modelling, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, cognitive processes and artificial intelligence, methodologies for net design, bio-inspired systems and engineering, and applications in a broad variety of fields.
Intelligent Information And Database Systems
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Author : Ngoc Thanh Nguyen
language : en
Publisher: Springer
Release Date : 2011-04-15
Intelligent Information And Database Systems written by Ngoc Thanh Nguyen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-15 with Computers categories.
The two-volume set LNAI 6591 and LNCS 6592 constitutes the refereed proceedings of the Third International Conference on Intelligent Information and Database Systems, ACIIDS 2011, held in Daegu, Korea, in April 2011. The 110 revised papers presented together with 2 keynote speeches were carefully reviewed and selected from 310 submissions. The papers are thematically divided into two volumes; they cover the following topics: intelligent database systems, data warehouses and data mining, natural language processing and computational linguistics, semantic Web, social networks and recommendation systems, technologies for intelligent information systems, collaborative systems and applications, e-business and e-commerce systems, e-learning systems, information modeling and requirements engineering, information retrieval systems, intelligent agents and multi-agent systems, intelligent information systems, intelligent internet systems, intelligent optimization techniques, object-relational DBMS, ontologies and knowledge sharing, semi-structured and XML database systems, unified modeling language and unified processes, Web services and semantic Web, computer networks and communication systems.