Interpretable support vector machines for functional data
نویسندگان
چکیده
منابع مشابه
Interpretable support vector machines for functional data
Support Vector Machines (SVM) has been shown to be a powerful nonparametric classification technique even for high-dimensional data. Although predictive ability is important, obtaining an easy-to-interpret classifier is also crucial in many applications. Linear SVM provides a classifier based on a linear score. In the case of functional data, the coefficient function that defines such linear sc...
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ژورنال
عنوان ژورنال: European Journal of Operational Research
سال: 2014
ISSN: 0377-2217
DOI: 10.1016/j.ejor.2012.08.017