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A Dependence Stability Bound based on the VC Dimension for Relational Classification
2015
International Journal of Database Theory and Application
Relational classification (RC) is concerned with the application of statistical learning to relational data. RC models do not have improved stability to smooth the perturbations generated by variations in the correlation between the relational data. Therefore, few studies have attempted to derive a bound and develop a stability learning framework for RC models. To solve this problem, we derive a learning bound with a new measure dependence stability and a limited Vapnik-Chervonenkis (VC)
doi:10.14257/ijdta.2015.8.3.11
fatcat:tjonthkl7vdrbgknavwng5hkv4