Nonlinear Dimensionality Reduction Techniques : A Data Structure Preservation Approach

Name: Nonlinear Dimensionality Reduction Techniques
Brand: Springer Nature Switzerland AG
SKU: 9783030810283
Price: 19800 KES
Availability: OutOfStock
ISBN: 9783030810283

2022 ed.

by Benoit Colange , Denys Dutykh , Sylvain Lespinats

Book Details

Format Paperback / softback

ISBN-10 3030810283

ISBN-13 9783030810283

Edition 2022 ed.

Publisher Springer Nature Switzerland AG

Imprint Springer Nature Switzerland AG

Country of Manufacture GB

Country of Publication GB

Publication Date Dec 4th, 2022

Print length 247 Pages

Product Classification: Information theory Imaging systems & technology Imaging systems and technology Algorithms & data structures Algorithms and data structures Machine learning Computer vision Digital signal processing (DSP)Signal processing

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This book proposes tools for analysis of multidimensional and metric data, by establishing a state-of-the-art of the existing solutions and developing new ones. This book reviews existing techniques for visual data exploration and dimensionality reduction such as tSNE and Isomap, and proposes new solutions to challenges in that field.

This book proposes tools for analysis of multidimensional and metric data, by establishing a state-of-the-art of the existing solutions and developing new ones. It mainly focuses on visual exploration of these data by a human analyst, relying on a 2D or 3D scatter plot display obtained through Dimensionality Reduction.

Performing diagnosis of an energy system requires identifying relations between observed monitoring variables and the associated internal state of the system. Dimensionality reduction, which allows to represent visually a multidimensional dataset, constitutes a promising tool to help domain experts to analyse these relations. This book reviews existing techniques for visual data exploration and dimensionality reduction such as tSNE and Isomap, and proposes new solutions to challenges in that field.

In particular, it presents the new unsupervised technique ASKI and the supervised methods ClassNeRV and ClassJSE. Moreover, MING, a new approach for local map quality evaluation is also introduced. These methods are then applied to the representation of expert-designed fault indicators for smart-buildings, I-V curves for photovoltaic systems and acoustic signals for Li-ion batteries.

Get Nonlinear Dimensionality Reduction Techniques by Benoit Colange, Denys Dutykh at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Springer Nature Switzerland AG and it has 247 pages.