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Support Vector Machines for Pattern Classification
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. T...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Springer London : Imprint: Springer,
2005.
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| Edición: | 1st ed. 2005. |
| Colección: | Advances in Computer Vision and Pattern Recognition,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-1-84628-219-5 | ||
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| 020 | |a 9781846282195 |9 978-1-84628-219-5 | ||
| 024 | 7 | |a 10.1007/1-84628-219-5 |2 doi | |
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| 100 | 1 | |a Abe, Shigeo. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Support Vector Machines for Pattern Classification |h [electronic resource] / |c by Shigeo Abe. |
| 250 | |a 1st ed. 2005. | ||
| 264 | 1 | |a London : |b Springer London : |b Imprint: Springer, |c 2005. | |
| 300 | |a XIV, 344 p. 110 illus. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Advances in Computer Vision and Pattern Recognition, |x 2191-6594 | |
| 505 | 0 | |a Two-Class Support Vector Machines -- Multiclass Support Vector Machines -- Variants of Support Vector Machines -- Training Methods -- Feature Selection and Extraction -- Clustering -- Kernel-Based Methods -- Maximum-Margin Multilayer Neural Networks -- Maximum-Margin Fuzzy Classifiers -- Function Approximation. | |
| 520 | |a 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]. | ||
| 650 | 0 | |a Pattern recognition systems. | |
| 650 | 0 | |a Natural language processing (Computer science). | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Control engineering. | |
| 650 | 0 | |a Robotics. | |
| 650 | 0 | |a Automation. | |
| 650 | 1 | 4 | |a Automated Pattern Recognition. |
| 650 | 2 | 4 | |a Natural Language Processing (NLP). |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Control, Robotics, Automation. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9781848008342 |
| 776 | 0 | 8 | |i Printed edition: |z 9781849969635 |
| 776 | 0 | 8 | |i Printed edition: |z 9781852339296 |
| 830 | 0 | |a Advances in Computer Vision and Pattern Recognition, |x 2191-6594 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/1-84628-219-5 |z Texto Completo |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||