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Published in:
Brave New Realtime World: Introduction Read chapter Read first chapter

2013 | OriginalPaper | Chapter

7. Breaking Dimensions: Adaptive Scoring with Sparse Grids

Authors : Alexander Paprotny, Michael Thess

Published in: Realtime Data Mining

Publisher: Springer International Publishing

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Abstract

We introduce the concept of a sparse grid and show how this powerful approach to function space discretization may be employed to tackle high-dimensional machine learning problems of regression and classification. In particular, we address the issue of incremental computation of sparse grid regression coefficients so as to meet the requirements of realtime data mining. Conclusively, we present experimental results on real-world data sets.

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Metadata
Title
Breaking Dimensions: Adaptive Scoring with Sparse Grids
Authors
Alexander Paprotny
Michael Thess
Copyright Year
2013
Publisher
Springer International Publishing
Book
Realtime Data Mining

Print ISBN: 978-3-319-01320-6

Electronic ISBN: 978-3-319-01321-3

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-319-01321-3_7

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