A learning algorithm combining functional discriminant coordinates and functional principal components

• Autorzy: Tomasz Górecki , Mirosław Krzyśko
• Języki publikacji: EN

Abstrakty

EN

A new type of discriminant space for functional data is presented, combining the advantages of a functional discriminant coordinate space and a functional principal component space. In order to provide a comprehensive comparison, we conducted a set of experiments, testing effectiveness on 35 functional data sets (time series). Experiments show that constructed combined space provides a higher quality of classification of LDA method compared with component spaces.

Słowa kluczowe

EN

functional principal components; functional discriminant coordinates

Kategorie tematyczne

• 62H25: Factor analysis and principal components; correspondence analysis
• 62H30: Classification and discrimination; cluster analysis
• 68T10: Pattern recognition, speech recognition

• Wydawca: Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra
• Czasopismo: Discussiones Mathematicae Probability and Statistics
• Rocznik: 2014
• Tom: 34
• Numer: 1-2
• Strony: 127-141

Daty

wydano

2014

otrzymano

2014-09-10

poprawiono

2014-09-16

Twórcy

autor

Tomasz Górecki

• Adam Mickiewicz University, Faculty of Mathematics and Computer Science, Umultowska 87, 61-614 Poznań, Poland

autor

Mirosław Krzyśko

• Adam Mickiewicz University, Faculty of Mathematics and Computer Science, Umultowska 87, 61-614 Poznań, Poland
• President Stanisław Wojciechowski Higher Vocational State School in Kalisz, Faculty of Management, Nowy Świat 4, 62-800 Kalisz, Poland

Bibliografia

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Identyfikatory

DOI

10.7151/dmps1163