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Multiclass functional discriminant analysis and its application to gesture recognition. (English) Zbl 1226.62061

Summary: We consider applying a functional logistic discriminant procedure to the analysis of handwritten character data. Time-course trajectories corresponding to the X and Y coordinate values of handwritten characters written in the air with one finger are converted into a functional data set via regularized basis expansion. We then apply functional logistic modeling to classify the functions into several classes. In order to select the values of adjusted parameters involved in the functional logistic model, we derive a model selection criterion for evaluating models estimated by the method of regularization. Results indicate the effectiveness of our modeling strategy in terms of prediction accuracy.

MSC:

62H30 Classification and discrimination; cluster analysis (statistical aspects)
68T10 Pattern recognition, speech recognition
62J12 Generalized linear models (logistic models)
65C60 Computational problems in statistics (MSC2010)

Software:

PRMLT; fda (R)
Full Text: DOI

References:

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