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Splitting of calibration data by cluster analysis
Author(s) -
Naes Tormod,
Isaksson Tomas
Publication year - 1991
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.1180050106
Subject(s) - mahalanobis distance , residual , calibration , cluster analysis , mathematics , cluster (spacecraft) , linearity , data mining , regression , statistics , algorithm , computer science , pattern recognition (psychology) , artificial intelligence , engineering , electrical engineering , programming language
Abstract The topic of the present paper is the splitting of calibration data into subgroups with improved linearity in each group. The method proposed is based on a criterion which is a weighted average of a Mahalanobis distance and a squared regression residual. The algorithm used to find the solution is based on fuzzy clustering. Two examples are given to illustrate the theory.