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Title: A classification tree for functional data Authors:  Jan Gertheiss - Helmut Schmidt University (Germany) [presenting]
Annette Moeller - Clausthal University of Technology (Germany)
Abstract: Many standard tools for data analysis already have their functional counterparts tailored to the specific properties of functional data. We introduce a novel classification tree specifically designed to deal with functional predictors. Partitioning for a chosen predictor in a specific node of the tree is based on comparing each observational curve in that node to the class-specific mean in terms of a (functional) distance measure. A curve under consideration is assigned to the class to whose mean curve it is closest in terms of the chosen metric.