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Semi-supervised learning /
A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems, this text looks at state-of-the-art algorithms, applications benchmark experiments, and directions for future research.
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge, Mass. :
MIT Press,
©2006.
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| Colección: | Adaptive computation and machine learning.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Semi-supervised learning / |c [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien. |
| 260 | |a Cambridge, Mass. : |b MIT Press, |c ©2006. | ||
| 300 | |a 1 online resource (x, 508 pages) : |b illustrations | ||
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| 490 | 1 | |a Adaptive computation and machine learning | |
| 504 | |a Includes bibliographical references (pages 479-497). | ||
| 588 | 0 | |a Print version record. | |
| 520 | 8 | |a A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems, this text looks at state-of-the-art algorithms, applications benchmark experiments, and directions for future research. | |
| 505 | 0 | |a Series Foreword; Preface; 1 -- Introduction to Semi-Supervised Learning; 2 -- A Taxonomy for Semi-Supervised Learning Methods; 3 -- Semi-Supervised Text Classification Using EM; 4 -- Risks of Semi-Supervised Learning: How Unlabeled Data Can Degrade Performance of Generative Classifiers; 5 -- Probabilistic Semi-Supervised Clustering with Constraints; 6 -- Transductive Support Vector Machines; 7 -- Semi-Supervised Learning Using Semi- Definite Programming; 8 -- Gaussian Processes and the Null-Category Noise Model; 9 -- Entropy Regularization; 10 -- Data-Dependent Regularization. | |
| 505 | 8 | |a 11 -- Label Propagation and Quadratic Criterion12 -- The Geometric Basis of Semi-Supervised Learning; 13 -- Discrete Regularization; 14 -- Semi-Supervised Learning with Conditional Harmonic Mixing; 15 -- Graph Kernels by Spectral Transforms; 16- Spectral Methods for Dimensionality Reduction; 17 -- Modifying Distances; 18 -- Large-Scale Algorithms; 19 -- Semi-Supervised Protein Classification Using Cluster Kernels; 20 -- Prediction of Protein Function from Networks; 21 -- Analysis of Benchmarks; 22 -- An Augmented PAC Model for Semi- Supervised Learning. | |
| 505 | 8 | |a 23 -- Metric-Based Approaches for Semi- Supervised Regression and Classification24 -- Transductive Inference and Semi-Supervised Learning; 25 -- A Discussion of Semi-Supervised Learning and Transduction; References; Notation and Symbols; Contributors; Index. | |
| 546 | |a English. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
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| 650 | 0 | |a Supervised learning (Machine learning) | |
| 650 | 6 | |a Apprentissage supervisé (Intelligence artificielle) | |
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| 650 | 7 | |a COMPUTERS |x Intelligence (AI) & Semantics. |2 bisacsh | |
| 650 | 7 | |a Supervised learning (Machine learning) |2 fast | |
| 653 | |a COMPUTER SCIENCE/Machine Learning & Neural Networks | ||
| 700 | 1 | |a Chapelle, Olivier. | |
| 700 | 1 | |a Schölkopf, Bernhard. | |
| 700 | 1 | |a Zien, Alexander. | |
| 758 | |i has work: |a Semi-supervised learning (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGFQqvqhPRRX4gg9XkPrtq |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
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| 830 | 0 | |a Adaptive computation and machine learning. | |
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