A learning algorithm combining functional discriminant coordinates and functional principal components
Tomasz Górecki, Mirosław Krzyśko (2014)
Discussiones Mathematicae Probability and Statistics
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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.