A learning algorithm combining functional discriminant coordinates and functional principal components
Tomasz Górecki ; Mirosław Krzyśko
Discussiones Mathematicae Probability and Statistics, Tome 34 (2014), p. 127-141 / Harvested from The Polish Digital Mathematics Library
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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.

Publié le : 2014-01-01
EUDML-ID : urn:eudml:doc:270840 
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     author = {Tomasz G\'orecki and Miros\l aw Krzy\'sko},
     title = {A learning algorithm combining functional discriminant coordinates and functional principal components},
     journal = {Discussiones Mathematicae Probability and Statistics},
     volume = {34},
     year = {2014},
     pages = {127-141},
     zbl = {1326.62135},
     language = {en},
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Tomasz Górecki; Mirosław Krzyśko. A learning algorithm combining functional discriminant coordinates and functional principal components. Discussiones Mathematicae Probability and Statistics, Tome 34 (2014) pp. 127-141. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1163/

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