{"product_id":"nonlinear-dimensionality-reduction-techniques-a-data-structure-preservation-approach-9783030810252","title":"Nonlinear Dimensionality Reduction Techniques: A Data Structure Preservation Approach","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book provides tools for analyzing multidimensional and metric data, focusing on visual exploration through dimensionality reduction. It reviews existing techniques and proposes new solutions, such as ASKI, ClassNeRV, ClassJSE, and MING, for representing expert-designed fault indicators, I-V curves, and acoustic signals. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 247 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 03 December 2021\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer Nature Switzerland AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThis comprehensive book offers a valuable resource for researchers and practitioners seeking advanced tools and techniques for analyzing multidimensional and metric data. By providing a state-of-the-art overview of existing solutions and developing innovative new ones, it empowers users to effectively explore and understand these complex data sets.\u003cbr\u003e\u003cbr\u003eThe book's primary focus lies in facilitating visual exploration of multidimensional and metric data by human analysts. It relies on the generation of 2D or 3D scatter plot displays through dimensionality reduction techniques, enabling domain experts to analyze the relationships between observed monitoring variables and the underlying internal state of the system.\u003cbr\u003e\u003cbr\u003eDimensionality reduction plays a crucial role in this analysis, as it allows for the representation of visually a multidimensional dataset, making it easier for experts to identify patterns, trends, and correlations. The book reviews existing techniques for visual data exploration and dimensionality reduction, including t-SNE and Isomap, and proposes novel solutions to address challenges in this field.\u003cbr\u003e\u003cbr\u003eIn particular, the book introduces the new unsupervised technique called ASKI, as well as the supervised methods ClassNeRV and ClassJSE. Additionally, a novel approach for local map quality evaluation called MING is presented. These methods are then applied to diverse real-world applications, such as the representation of expert-designed fault indicators for smart buildings, I-V curves for photovoltaic systems, and acoustic signals for Li-ion batteries.\u003cbr\u003e\u003cbr\u003eBy presenting a wealth of practical examples and case studies, this book demonstrates the practical utility and effectiveness of the proposed techniques in various domains. It serves as a valuable guide for researchers, engineers, and practitioners interested in advancing their understanding and expertise in multidimensional data analysis.\u003cbr\u003e\u003cbr\u003eOverall, this book is a must-read for anyone seeking to leverage the power of advanced analytics and visualization to extract meaningful insights from multidimensional and metric data. Its comprehensive coverage, innovative approaches, and practical applications make it an invaluable resource for researchers, practitioners, and students alike.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 606g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783030810252\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Sylvain Lespinats,Benoit Colange,Denys Dutykh","offers":[{"title":"Hardback","offer_id":44103160660218,"sku":"9783030810252","price":91.62,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1646388106612_book.jpg?v=1646988141","url":"https:\/\/shulphink.com\/products\/nonlinear-dimensionality-reduction-techniques-a-data-structure-preservation-approach-9783030810252","provider":"Shulph Ink","version":"1.0","type":"link"}