- Autor
- Krzyśko Mirosław (Adam Mickiewicz University in Poznań, Poland), Waszak Łukasz (Adam Mickiewicz University in Poznań, Poland)
- Tytuł
- Methods of Representation for Kernel Canonical Correlation Analysis
- Źródło
- Statistics in Transition, 2012, vol. 13, nr 2, s. 301-310, bibliogr. 5 poz.
- Słowa kluczowe
- Analiza korelacji, Przestrzeń Hilberta, Metody statystyczne
Correlation analysis, Hilbert Spaces, Statistical methods - Uwagi
- Materiały z Kongresu Statystyki Polskiej: The 100th Anniversary of the Polish Statistical Association, 2012.
summ. - Abstrakt
- Classical canonical correlation analysis seeks the associations between two data sets, i.e. it searches for linear combinations of the original variables having maximal correlation. Our task is to maximize this correlation. This problem is equivalent to solving the generalized eigenvalue problem. The maximal correlation coefficient (being a solution of this problem) is the first canonical correlation coefficient. In this paper we construct nonlinear canonical correlation analysis in reproducing kernel Hilbert spaces. The new kernel generalized eigenvalue problem always has the solution equal to one, and this is a typical case of over-fitting. We present methods to solve this problem and compare the results obtained by classical and kernel canonical correlation analysis. (original abstract)
- Dostępne w
- Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
Biblioteka Główna Uniwersytetu Ekonomicznego we Wrocławiu - Pełny tekst
- Pokaż
- Bibliografia
- ARONSZAJN, N. (1950): Theory of reproducing kernels, Transactions of the American Mathematical Society 68, 337-404.
- HARDLE, W., SIMAR, L. (2007): Applied Multivariate Statistical Analysis, Springer, 321-330 and 434-435.
- HOTELLING, H. (1936): Relation between two sets of variates, Biometrika 28, 321-377.
- PREDA, C. (2006): Regression models for functional data by reproducing kernel Hilbert spaces methods, Journal of Statistical Planning and Inference 137, 831.
- ZHENG, W., ZHOU, X., ZOU, C., ZHAO L. (2006): Facial Expression Recognition Using Kernel Canonical Correlation Analysis, IEEE Transaction on Neural Networks 17(1), 233.
- Cytowane przez
- ISSN
- 1234-7655
- Język
- eng