Penalized Bregman divergence for large-dimensional regression and classification
نویسندگان
چکیده
منابع مشابه
Penalized Bregman divergence for large-dimensional regression and classification.
Regularization methods are characterized by loss functions measuring data fits and penalty terms constraining model parameters. The commonly used quadratic loss is not suitable for classification with binary responses, whereas the loglikelihood function is not readily applicable to models where the exact distribution of observations is unknown or not fully specified. We introduce the penalized ...
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ژورنال
عنوان ژورنال: Biometrika
سال: 2010
ISSN: 1464-3510,0006-3444
DOI: 10.1093/biomet/asq033