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Non‐linear canonical correlation †
Author(s) -
Burg Eeke,
Leeuw Jan
Publication year - 1983
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1983.tb00765.x
Subject(s) - canonical correlation , scaling , mathematics , canonical analysis , correlation , stability (learning theory) , canonical form , linear correlation , statistics , computer science , pure mathematics , geometry , machine learning
Non‐linear canonical correlation analysis is a method for canonical correlation analysis with optimal scaling features. The method fits many kinds of discrete data. The different parameters are solved for in an alternating least squares way and the corresponding program is called CANALS. An application of CANALS is discussed and also a study of the stability of the scaling results.