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Some common misunderstandings in chemometrics
Author(s) -
Kjeldahl Karin,
Bro Rasmus
Publication year - 2010
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1346
Subject(s) - chemometrics , computer science , relation (database) , simple (philosophy) , component (thermodynamics) , software , data science , management science , data mining , machine learning , epistemology , engineering , philosophy , programming language , physics , thermodynamics
This paper describes a number of issues and tools in practical chemometric data analysis that are often either misunderstood or misused. Deciding what are relevant samples and variables, (mis‐)use of common model diagnostics, and interpretational issues are addressed in relation to component models such as PCA and PLS models. Along with simple misunderstandings, the use of chemometric software packages may contribute to the mistakes if not used critically, and it is thus a main conclusion that good data analysis practice requires the analyst to take responsibility and do what is relevant for the given purpose. Copyright © 2010 John Wiley & Sons, Ltd.