Hierarchical feature selection addresses the issues caused by the presence of high-dimensional features in multi-category classification systems with hierarchical structures. Granular calculations are made to analyze the hierarchical relationships among categories when selecting the optimal feature subset.
Firstly, a hierarchical structure is constructed via bottom-up multi-granularity clustering based on feature similarities rather than semantic categories. This ...
This clustering hierarchy is conducive to solving semantic gap problems in the existing hierarchy. Secondly, the optimal feature subset is selected using the ℓ1 ...
Hierarchical feature selection with multi-granularity clustering structure ... Liang, An efficient rough feature selection algorithm with a multi-granulation view ...
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Apr 20, 2021 · Hierarchical feature selection addresses the issues caused by the presence of high-dimensional features in multi-category classification ...
Guo, Shunxin, Zhao, Hong, Yang, Wenyuan (2021) Hierarchical feature selection with multi-granularity clustering structure. Information Sciences, 568. 448-462 ...
Apr 20, 2022 · To address these problems, we propose an online streaming feature selection framework with a hierarchical structure to solve the above two ...
In this paper, we propose a novel method to extract multi-granularity features based solely on the original input sentences. We show that effective structured ...
