Infinite Bayesian Max-Margin Discriminant Projection

In this article, considering the supervised dimensionality reduction, we first propose a model, called infinite Bayesian max-margin linear discriminant projection (iMMLDP), by assembling a set of local regions, where we make use of Bayesian nonparametric priors to handle the model selection problem,...

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Veröffentlicht in:	IEEE transactions on cybernetics 2022-05, Vol.52 (5), p.3936-3946
Hauptverfasser:	Wen, Wei, Chen, Bo, Cao, Xuefei, Zhang, Xuefeng, Wang, Zhengjue, Liu, Hongwei
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayes methods Bayesian analysis Clustering Data models Dimensionality reduction Dirichlet process (DP) mixture Kernel Kernels large margin Mathematical model Projection Radar imaging Reduction regularized Bayesian supervised feature extraction Support vector machines Task analysis
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