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A novel relational regularization feature selection method for joint regression and classification in AD diagnosis
2017
Medical Image Analysis
In this paper, we focus on joint regression and classification for Alzheimer's disease diagnosis and propose a new feature selection method by embedding the relational information inherent in the observations into a sparse multi-task learning framework. Specifically, the relational information includes three kinds of relationships (such as feature-feature relation, response-response relation, and sample-sample relation), for preserving three kinds of the similarity, such as for the features,
doi:10.1016/j.media.2015.10.008
pmid:26674971
pmcid:PMC4862945
fatcat:xdqesmpifvbuhmsquumrdbouki