caa a22 4500 606199284 CHVBK 20210128100937.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s11045-013-0240-9 doi (NATIONALLICENCE)springer-10.1007/s11045-013-0240-9 A logistic non-negative matrix factorization approach to binary data sets [Elektronische Daten] [A. Tomé, R. Schachtner, V. Vigneron, C. Puntonet, E. Lang] An analysis of binary data sets employing Bernoulli statistics and a partially non-negative factorization of the related matrix of log-odds is presented. The model places several constraints onto the factorization process rendering the estimated basis system strictly non-negative or even binary. Thereby the proposed model places itself in between a logistic PCA and a binary NMF approach. We show with proper toy data sets that different variants of the proposed model yield reasonable results and indeed are able to estimate with good precision the underlying basis system which forms a new and often more compact representation of the observations. An application of the method to the USPS data set reveals the performance of the various variants of the model and shows good reconstruction quality even with a low rank binary basis set. Springer Science+Business Media New York, 2013 Logistic PCA nationallicence Binary matrix factorization nationallicence Dimensionality reduction nationallicence Tomé A. IEETA, DETI, Universidade de Aveiro, 3810-193, Aveiro, Portugal aut Schachtner R. Infineon Technologies AG, 93049, Regensburg, Germany aut Vigneron V. IBISC, Université d'Evry Val d'Essonne, 91025, Evry Cedex, France aut Puntonet C. DATC, EEIS, Universidad de Granada, 38170, Granada, Spain aut Lang E. CIML Group, Biophysics Department, University of Regensburg, 93040, Regensburg, Germany aut Multidimensional Systems and Signal Processing Springer US; http://www.springer-ny.com 26/1(2015-01-01), 125-143 0923-6082 26:1<125 2015 26 11045 https://doi.org/10.1007/s11045-013-0240-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11045-013-0240-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Tomé A. IEETA, DETI, Universidade de Aveiro, 3810-193, Aveiro, Portugal aut NATIONALLICENCE 700 1- Schachtner R. Infineon Technologies AG, 93049, Regensburg, Germany aut NATIONALLICENCE 700 1- Vigneron V. IBISC, Université d'Evry Val d'Essonne, 91025, Evry Cedex, France aut NATIONALLICENCE 700 1- Puntonet C. DATC, EEIS, Universidad de Granada, 38170, Granada, Spain aut NATIONALLICENCE 700 1- Lang E. CIML Group, Biophysics Department, University of Regensburg, 93040, Regensburg, Germany aut NATIONALLICENCE 773 0- Multidimensional Systems and Signal Processing Springer US; http://www.springer-ny.com 26/1(2015-01-01), 125-143 0923-6082 26:1<125 2015 26 11045