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An improved multi-label classification method and its application to functional genomics
2010
International Journal of Computational Biology and Drug Design
In this paper, a multi-label classification method based on label ranking and delicate boundary Support Vector Machine (SVM) is proposed for solving the functional genomics applications. Firstly, an improved probabilistic SVM with delicate decision boundary is used as scoring approach to obtain a proper label rank. Secondly, an instance-dependent thresholding strategy is proposed to decide classification results. A d-folds validation approach is utilised to determine a set of target thresholds
doi:10.1504/ijcbdd.2010.035239
pmid:20852337
fatcat:aybukm3ffncutna7h6sbdqxtfe