...Yifeng Zheng; Xianlong Zeng; Wenjie Zhang; Baoya Wei; Weishuo Ren; Depeng Qing Purpose As intelligent technology advances, practical applications often involve data with multiple labels. Therefore, multi-label feature selection methods have attracted much attention to extract valuable information...

... Optimization with Feature Selection (GWOFS) and multilayer perceptron (MLP) for SDP. The GWOFS-MLP hybrid model is designed to optimize feature selection, ultimately enhancing the accuracy and efficiency of SDP. Grey Wolf Optimization, inspired by the social hierarchy and hunting behavior of grey wolves...

... to compromised performance and efficiency. Design/methodology/approach To address this issue, this paper proposes a novel method called Manifold Embedded Discriminative Feature Selection (MEDFS) to select global and local features, thereby reducing the dimensionality of the feature representation...

... to the establishment of more non-complex models.ing, test and overall dataset to check every model's efficiency. Dimension reduction Metaheuristic algorithms MARS Feature selection BIST 100 A correlation-based feature selection algorithm (CFS) was developed to perform dimension reduction using...

... for feature selection and weighting, Alford et al. (2012a) compared the performances of three GEBAs for multibiometric feature selection and weighting. The first GEBA, referred to as genetic and evolutionary feature selection (GEFeS), evolves subsets of the most salient biometric features...