Open AccessNon-linear PCA: a missing data approach
Author(s) -
Matthias Scholz,
Fatma Kaplan,
Charles L. Guy,
Joachim Kopka,
Joachim Selbig
Publication year - 2005
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bti634
Subject(s) - missing data , computer science , data mining , principal component analysis , artificial intelligence , machine learning
Visualizing and analysing the potential non-linear structure of a dataset is becoming an important task in molecular biology. This is even more challenging when the data have missing values.
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