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2017 | OriginalPaper | Chapter

Biclustering Based on Collinear Patterns

Author : Leon Bobrowski

Published in: Bioinformatics and Biomedical Engineering

Publisher: Springer International Publishing

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Abstract

Data mining technique based on minimization of the convex and piecewise linear (CPL) criterion functions can be used to extract collinear (flat) patterns from large, multidimensional data sets. Flat patterns consist of data vectors located on planes in a multidimensional feature space. Data subsets located on such planes can represent linear interactions between multiple variables (features). New method of collinear biclustering can also be developed through this technique.

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previous chapter Diagnosis of Auditory Pathologies with Hidden Markov Models
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Metadata
Title
Biclustering Based on Collinear Patterns
Author
Leon Bobrowski
Copyright Year
2017
Book
Bioinformatics and Biomedical Engineering

Print ISBN: 978-3-319-56147-9

Electronic ISBN: 978-3-319-56148-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-56148-6_11

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