Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery

Research article (Expert Systems with Applications, 2016) · cited 104× · AI/ML
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Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery

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Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery. Retrieved May 24, 2026, from https://4ort.xyz/entity/attribute-clustering-using-rough-set-theory-for-feature-selection-in-fault-severity-classification-of-rotating-machinery
MLA “Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/attribute-clustering-using-rough-set-theory-for-feature-selection-in-fault-severity-classification-of-rotating-machinery.
BibTeX @misc{4ortxyz_attribute-clustering-using-rough-set-theory-for-feature-selection-in-fault-severity-classification-of-rotating-machinery_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery}}, year = {2026}, url = {https://4ort.xyz/entity/attribute-clustering-using-rough-set-theory-for-feature-selection-in-fault-severity-classification-of-rotating-machinery}, note = {Accessed: 2026-05-24}}
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