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Graph-Embedded Multi-layer Kernel Extreme Learning Machine for One-class Classification or (Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification)
[article]
2019
arXiv
pre-print
A brain can detect outlier just by using only normal samples. Similarly, one-class classification (OCC) also uses only normal samples to train the model and trained model can be used for outlier detection. In this paper, a multi-layer architecture for OCC is proposed by stacking various Graph-Embedded Kernel Ridge Regression (KRR) based Auto-Encoders in a hierarchical fashion. These Auto-Encoders are formulated under two types of Graph-Embedding, namely, local and global variance-based
arXiv:1904.06491v1
fatcat:k3j6jfyjrzeozi4nlv4wm6scju