A note on variable selection in functional regression via random subspace method
نویسندگان
چکیده
منابع مشابه
Random subspace method for multivariate feature selection
In a growing number of domains the data collected has a large number of features. This poses a challenge to classical pattern recognition techniques, since the number of samples often is still limited with respect to the feature size. Classical pattern recognition methods suffer from the small sample size, and robust classification techniques are needed. In order to reduce the dimensionality of...
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For regression models with functional responses and scalar predictors, it is common for the number of predictors to be large. Despite this, few methods for variable selection exist for function-on-scalar models, and none account for the inherent correlation of residual curves in such models. By expanding the coefficient functions using a B-spline basis, we pose the function-on-scalar model as a...
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ژورنال
عنوان ژورنال: Statistical Methods & Applications
سال: 2018
ISSN: 1618-2510,1613-981X
DOI: 10.1007/s10260-018-0421-7