A-Stacking and A-Bagging: Adaptive versions of ensemble learning algorithms for spoof fingerprint detection

作者：

Highlights：

• The behavior of stacking and bagging on spoof fingerprint detection is explored.

• Adaptive versions of stacking and bagging are proposed.

• Diversity is achieved by generating an ensemble of disjoint base classifiers.

• Empirical results are provided on class balanced and imbalanced datasets.

摘要

•The behavior of stacking and bagging on spoof fingerprint detection is explored.•Adaptive versions of stacking and bagging are proposed.•Diversity is achieved by generating an ensemble of disjoint base classifiers.•Empirical results are provided on class balanced and imbalanced datasets.

论文关键词：Stacking,Bagging,Ensemble learning,Spoof fingerprint detection

论文评审过程：Received 16 May 2019, Revised 18 December 2019, Accepted 21 December 2019, Available online 24 December 2019, Version of Record 6 January 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.113160