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.
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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.
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Add this copy of Understanding High-Dimensional Spaces to cart. $65.43, like new condition, Sold by GreatBookPricesUK5 rated 5.0 out of 5 stars, ships from Castle Donington, DERBYSHIRE, UNITED KINGDOM, published 2012 by Springer-Verlag Berlin and Heidelberg GmbH & Co. K.
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2012, Springer-Verlag Berlin and Heidelberg GmbH & Co. K
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Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Published:
2012
Language:
English
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Add this copy of Understanding High-Dimensional Spaces to cart. $60.65, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2012 by Springer-Verlag Berlin and Heidelberg GmbH & Co. K.
Edition:
2012, Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Publisher:
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Published:
2012
Language:
English
Alibris ID:
11476740088
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Edition:
2012, Springer-Verlag Berlin and Heidelberg GmbH & Co. K
