Class imbalance

Effective sample selection for classification of pre-miRNAs

K. Han, Effective sample selection for classification of pre-miRNAs, vol. 10, pp. 506-518, 2011.

To solve the class imbalance problem in the classification of pre-miRNAs with the ab initio method, we developed a novel sample selection method according to the characteristics of pre-miRNAs. Real/pseudo pre-miRNAs are clustered based on their stem similarity and their distribution in high dimensional sample space, respectively. The training samples are selected according to the sample density of each cluster. Experimental results are validated by the cross-validation and other testing datasets composed of human real/pseudo pre-miRNAs.

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