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Conference papers
A Proposition for Fixing the Dimensionality of a Laplacian Low-rank Approximation of any Binary Data-matrix
Abstract : Laplacian low-rank approximations are much appreciated in the context of graph spectral methods and Correspondence Analysis. We address here the problem of determining the dimensionality K* of the relevant eigenspace of a general binary datatable by a statistically well-founded method. We propose 1) a general framework for graph adjacency matrices and any rectangular binary matrix, 2) a randomization test for fixing K*. We illustrate with both artificial and real data.
Cited literature [18 references]
https://hal.archives-ouvertes.fr/hal-00773436
Contributor : Martine Cadot <>
Submitted on : Tuesday, March 19, 2013 - 8:34:10 PM
Last modification on : Tuesday, October 27, 2020 - 2:34:29 PM
Long-term archiving on: : Thursday, June 20, 2013 - 4:21:32 PM
Contributor : Martine Cadot <>
Submitted on : Tuesday, March 19, 2013 - 8:34:10 PM
Last modification on : Tuesday, October 27, 2020 - 2:34:29 PM
Long-term archiving on: : Thursday, June 20, 2013 - 4:21:32 PM
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eKnow013_lelu_cadot_OK2.pdf
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