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Autor(en):
Gutch, H. W.; Krumsiek, J.; Theis, F. J. 
Titel:
An ISA algorithm with unknown group sizes successfully identifies biologically meaningful clusters in metabolomics data 
Abstract:
Independent Subspace Analysis (ISA) denotes the task of linearly separating multivariate observations into statistically independent multi-dimensional sources, where dependencies only exist within these subspaces but not between them. So far ISA algorithms have mostly been described in the context of known group sizes. Here, we extend a previously proposed ISA algorithm based on joint block di-agonalization of 4-th order cumulant matrices to separate subspaces of unknown sizes. Further automated...    »
 
Verlag / Institution:
EUSIPCO 
Verlagsort:
Barcelona 
Jahr:
2011 
Seiten:
1733-1737