Financial Pattern Recognition Using Support Vector Machines

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Financial Pattern Recognition Using Support Vector Machines

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Author : A. Fan
language : en
Publisher:
Release Date : 2001

Financial Pattern Recognition Using Support Vector Machines written by A. Fan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Corporations categories.

Support Vector Machines For Pattern Classification

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Author : Shigeo Abe
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-28

Support Vector Machines For 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 2005-12-28 with Computers categories.

I was shocked to see a student’s report on performance comparisons between support vector machines (SVMs) and fuzzy classi?ers that we had developed withourbestendeavors.Classi?cationperformanceofourfuzzyclassi?erswas comparable, but in most cases inferior, to that of support vector machines. This tendency was especially evident when the numbers of class data were small. I shifted my research e?orts from developing fuzzy classi?ers with high generalization ability to developing support vector machine–based classi?ers. This book focuses on the application of support vector machines to p- tern classi?cation. Speci?cally, we discuss the properties of support vector machines that are useful for pattern classi?cation applications, several m- ticlass models, and variants of support vector machines. To clarify their - plicability to real-world problems, we compare performance of most models discussed in the book using real-world benchmark data. Readers interested in the theoretical aspect of support vector machines should refer to books such as [109, 215, 256, 257].

Pattern Recognition With Support Vector Machines

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Author : Alessandro Verri
language : en
Publisher:
Release Date : 2002

Pattern Recognition With Support Vector Machines written by Alessandro Verri 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.

Pattern Recognition With Support Vector Machines

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Author : Seong-Whan Lee
language : en
Publisher: Springer
Release Date : 2003-08-02

Pattern Recognition With Support Vector Machines written by Seong-Whan Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-08-02 with Computers categories.

This book constitutes the refereed proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines, SVM 2002, held in Niagara Falls, Canada in August 2002.The 16 revised full papers and 14 poster papers presented together with two invited contributions were carefully reviewed and selected from 57 full paper submissions. The papers presented span the whole range of topics in pattern recognition with support vector machines from computational theories to implementations and applications.

Pattern Recognition Using Support Vector Machines

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Author :
language : en
Publisher:
Release Date : 2002

Pattern Recognition Using Support Vector Machines written by 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.

Advances In Pattern Recognition And Artificial Intelligence

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Author : Marleah Blom
language : en
Publisher: World Scientific
Release Date : 2021-11-16

Advances In Pattern Recognition And Artificial Intelligence written by Marleah Blom and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-16 with Computers categories.

This book includes reviewed papers by international scholars from the 2020 International Conference on Pattern Recognition and Artificial Intelligence (held online). The papers have been expanded to provide more details specifically for the book. It is geared to promote ongoing interest and understanding about pattern recognition and artificial intelligence. Like the previous book in the series, this book covers a range of topics and illustrates potential areas where pattern recognition and artificial intelligence can be applied. It highlights, for example, how pattern recognition and artificial intelligence can be used to classify, predict, detect and help promote further discoveries related to credit scores, criminal news, national elections, license plates, gender, personality characteristics, health, and more.Chapters include works centred on medical and financial applications as well as topics related to handwriting analysis and text processing, internet security, image analysis, database creation, neural networks and deep learning. While the book is geared to promote interest from the general public, it may also be of interest to graduate students and researchers in the field.

Bio Inspired Credit Risk Analysis

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Author : Lean Yu
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-04-24

Bio Inspired Credit Risk Analysis written by Lean 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 2008-04-24 with Business & Economics categories.

Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.

Pattern Recognition With Support Vector Machines

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Author : Seong-Whan Lee
language : en
Publisher: Springer
Release Date : 2014-03-12

Pattern Recognition With Support Vector Machines written by Seong-Whan Lee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-12 with Computers categories.

Support Vector Machines Applications

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Author : Yunqian Ma
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-02-12

Support Vector Machines Applications written by Yunqian Ma 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 2014-02-12 with Technology & Engineering categories.

Support vector machines (SVM) have both a solid mathematical background and practical applications. This book focuses on the recent advances and applications of the SVM, such as image processing, medical practice, computer vision, and pattern recognition, machine learning, applied statistics, and artificial intelligence. The aim of this book is to create a comprehensive source on support vector machine applications.

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.