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A linear functional strategy for regularized ranking
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DOI：10.1016/j.neunet.2015.08.012.png)
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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. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
Regularization
Ill-posed problem
Ranking
Linear functional strategy
Diabetes technology
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