Titlebook: Neural Information Processing; 25th International C Long Cheng,Andrew Chi Sing Leung,Seiichi Ozawa Conference proceedings 2018 Springer Nat

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Feature Selection Based on Fuzzy Conditional Distinction Degreeon entropy exploit the correlations between features and labels, lacking of taking into account the relevance between features. In this paper, we propose a new index for feature selection, named fuzzy conditional distinction degree (FDD), based on fuzzy similarity relation by combining feature corre

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Multi-label Feature Selection Method Based on Multivariate Mutual Information and Particle Swarm Optputational burdens, improve classification performance and enhance model interpretability, in multi-label learning. Mutual information (MI) between two random variables is widely used to describe feature-label relevance and feature-feature redundancy. Furthermore, multivariate mutual information (MM

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Adaptive Fuzzy Clustering Algorithm with Local Information and Markov Random Field for Image Segment obtain satisfactory performance for image segmentation under intense noise condition. This paper presents a novel local spatial information based fuzzy c-means clustering and Markov random field method for image segmentation. In the method, a new dissimilarity function is proposed by using the prio

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