کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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403816 | 677357 | 2016 | 10 صفحه PDF | دانلود رایگان |
Regularization schemes are frequently used for performing ranking tasks. This topic has been intensively studied in recent years. However, to be effective a regularization scheme should be equipped with a suitable strategy for choosing a regularization parameter. In the present study we discuss an approach, which is based on the idea of a linear combination of regularized rankers corresponding to different values of the regularization parameter. The coefficients of the linear combination are estimated by means of the so-called linear functional strategy. We provide a theoretical justification of the proposed approach and illustrate them by numerical experiments. Some of them are related with ranking the risk of nocturnal hypoglycemia of diabetes patients.
Journal: Neural Networks - Volume 73, January 2016, Pages 26–35