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Some features speak loud, but together they all speak louder: A study on the correlation between classification error and feature usage in decision-tree classification ensembles
Research article (Engineering Applications of Artificial Intelligence, 2017) · cited 18× · AI/ML
Some features speak loud, but together they all speak louder: A study on the correlation between classification error and feature usage in decision-tree classification ensembles
Summary
Some features speak loud, but together they all speak louder: A study on the correlation between classification error and feature usage in decision-tree classification ensembles is a scholarly article[1].
Key Facts
Some features speak loud, but together they all speak louder: A study on the correlation between classification error and feature usage in decision-tree classification ensembles's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Some features speak loud, but together they all speak louder: A study on the correlation between classification error and feature usage in decision-tree classification ensembles. Retrieved May 24, 2026, from https://4ort.xyz/entity/some-features-speak-loud-but-together-they-all-speak-louder-a-study-on-the-correlation-between-classification-error-and-
MLA“Some features speak loud, but together they all speak louder: A study on the correlation between classification error and feature usage in decision-tree classification ensembles.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/some-features-speak-loud-but-together-they-all-speak-louder-a-study-on-the-correlation-between-classification-error-and-.
BibTeX@misc{4ortxyz_some-features-speak-loud-but-together-they-all-speak-louder-a-study-on-the-correlation-between-classification-error-and-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Some features speak loud, but together they all speak louder: A study on the correlation between classification error and feature usage in decision-tree classification ensembles}}, year = {2026}, url = {https://4ort.xyz/entity/some-features-speak-loud-but-together-they-all-speak-louder-a-study-on-the-correlation-between-classification-error-and-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Some features speak loud, but together they all speak louder: A study on the correlation between classification error and feature usage in decision-tree classification ensembles — https://4ort.xyz/entity/some-features-speak-loud-but-together-they-all-speak-louder-a-study-on-the-correlation-between-classification-error-and- (retrieved 2026-05-24)
