Home ›
Entities
› academia
› Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach
Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach
Research article (IEEE Transactions on Cybernetics, 2015) · cited 52× · AI/ML
Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach
Summary
Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach is a scholarly article[1].
Key Facts
Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach. Retrieved May 24, 2026, from https://4ort.xyz/entity/identifying-quasi-equally-informative-subsets-in-feature-selection-problems-for-classification-a-max-relevance-min-redun
MLA“Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/identifying-quasi-equally-informative-subsets-in-feature-selection-problems-for-classification-a-max-relevance-min-redun.
BibTeX@misc{4ortxyz_identifying-quasi-equally-informative-subsets-in-feature-selection-problems-for-classification-a-max-relevance-min-redun_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach}}, year = {2026}, url = {https://4ort.xyz/entity/identifying-quasi-equally-informative-subsets-in-feature-selection-problems-for-classification-a-max-relevance-min-redun}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach — https://4ort.xyz/entity/identifying-quasi-equally-informative-subsets-in-feature-selection-problems-for-classification-a-max-relevance-min-redun (retrieved 2026-05-24)
