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Dimensionality Reduction with Unsupervised Nearest Neighbors

Language EnglishEnglish
Book Hardback
Book Dimensionality Reduction with Unsupervised Nearest Neighbors Oliver Kramer
Libristo code: 01663789
Publishers Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, May 2013
This book is devoted to a novel approach for dimensionality reduction based on the famous nearest ne... Full description
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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-word 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.§

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About the book

Full name Dimensionality Reduction with Unsupervised Nearest Neighbors
Author Oliver Kramer
Language English
Binding Book - Hardback
Date of issue 2013
Number of pages 132
EAN 9783642386510
ISBN 3642386512
Libristo code 01663789
Publishers Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Weight 3495
Dimensions 155 x 235 x 16

Categories

Technology, Engineering, Agriculture > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
Economics, Finance, Business & Management > Business & Management > Management & management techniques > Management decision making
Economics, Finance, Business & Management > Business & Management > Operational research
Mathematics & Science > Mathematics > Applied mathematics
Technology, Engineering, Agriculture > Technology: general issues > Engineering: general
Technology, Engineering, Agriculture > Technology: general issues > Maths for engineers
Computing & Information Technology > Computer science > Artificial intelligence
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