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Understanding High-Dimensional Spaces (SpringerBriefs in Computer Science)

David B. Skillicorn




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 | #3337563 in Books |  Springer |  2012-09-27 |  2012-09-27 | Original language:English | PDF # 1 |  9.25 x.28 x6.10l,.40 | File type: PDF | 108 pages

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|| ||From the reviews:Selected by Computing s as one of the Best s & Notable Books of 2013|“This brief eight-chapter book seeks to provide the reader with the tools to perform analysis of high-dimensional datasets and spaces. … book follows a very g

High-dimensional spaces arise as a way of modelling datasets with many attributes. Such a dataset can be directly represented in a space spanned by its attributes, with each record represented as a point in the space with its position depending on its attribute values. Such spaces are not easy to work with because of their high dimensionality: our intuition about space is not reliable, and measures such as distance do not provide as clear information as we might expec...

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