Dimensionality Reduction with Unsupervised Nearest Neighbors / / by Oliver Kramer
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| Autore: |
Kramer Oliver
|
| Titolo: |
Dimensionality Reduction with Unsupervised Nearest Neighbors / / by Oliver Kramer
|
| Pubblicazione: | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Edizione: | 1st ed. 2013. |
| Descrizione fisica: | 1 online resource (xviii, 130 pages) : illustrations (some color) |
| Disciplina: | 006.31 |
| 519.5/36 | |
| Soggetto topico: | Engineering mathematics |
| Engineering - Data processing | |
| Artificial intelligence | |
| Operations research | |
| Mathematical and Computational Engineering Applications | |
| Artificial Intelligence | |
| Operations Research and Decision Theory | |
| Note generali: | "ISSN: 1868-4394." |
| Nota di bibliografia: | Includes bibliographical references and index. |
| Nota di contenuto: | Part I Foundations -- Part II Unsupervised Nearest Neighbors -- Part III Conclusions. |
| Sommario/riassunto: | This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustrate the introduced concepts and to highlight the experimental results. . |
| Titolo autorizzato: | Dimensionality Reduction with Unsupervised Nearest Neighbors |
| ISBN: | 9783642386527 |
| 3642386520 | |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910438057103321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
Intelligent Systems Reference Library, . 1868-4408 ; ; 51