Open AccessLearning from missing data with the binary latent block model
Author(s) -
Gabriel Frisch,
Jean-Benoist Léger,
Yves Grandvalet
Publication year - 2021
Publication title -
statistics and computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.009
H-Index - 77
eISSN - 1573-1375
pISSN - 0960-3174
DOI - 10.1007/s11222-021-10058-y
Subject(s) - missing data , computer science , inference , binary data , cluster analysis , block (permutation group theory) , model selection , expectation–maximization algorithm , data mining , interpretation (philosophy) , artificial intelligence , voting , block model , data modeling , binary number , machine learning , mathematics , maximum likelihood , statistics , mining engineering , geometry , arithmetic , politics , political science , law , programming language , engineering , database
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