Mar 29, 2024 · In order to improve the classification accuracy of reduced sets, this paper starts from the idea of clustering and proposes a feature selection ...
Oct 22, 2024 · As a widely used data preprocessing method, feature selection with rough sets aims to delete redundant conditional features.
A group incremental feature selection based on knowledge granularity under the context of clustering · Baohua Liang, Yong Liu, +1 author. Houjiang He · Published ...
A group incremental feature selection based on knowledge granularity under the context of clustering. https://doi.org/10.1007/s13042-024-02113-7.
As a widely used data preprocessing method, feature selection with rough sets aims to delete redundant conditional features.
A group incremental feature selection based on knowledge granularity under the context of clustering. Baohua Liang; Yong Liu; Houjiang He. Original Article 29 ...
This algorithm devotes to find an effective feature subset in in a much shorter time when objects are added in groups. On this basis, Jing et al. presents an ...
We develop triple nested equivalence class (TNEC) RST for a group incremental approach to feature selection.
When a group of objects are added to a decision table, this work introduces incremental mechanisms for three representative information entropies and ...
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Mar 15, 2024 · This paper presents a novel framework for continual feature selection (CFS) in data preprocessing, particularly in the context of an open ...