Real membership authentication applications require machines to learn from stream data while making a decision as accurately as possible whenever the authentication is needed. To achieve that, we proposed a novel algorithm which authenticated membership by a one-pass incremental principle component analysis(IPCA) learning. It is demonstrated that the proposed algorithm involves an useful incremental feature construction in membership authentication, and the incremental learning system works optimally due to its performance is converging to the performance of a batch learning system.
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