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Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data
Research article (Soil Dynamics and Earthquake Engineering, 2021) · cited 73× · AI/ML
Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data
Summary
Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data is a scholarly article[1].
Key Facts
Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data. Retrieved May 24, 2026, from https://4ort.xyz/entity/comparison-of-tree-based-machine-learning-algorithms-for-predicting-liquefaction-potential-using-canonical-correlation-f
MLA“Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/comparison-of-tree-based-machine-learning-algorithms-for-predicting-liquefaction-potential-using-canonical-correlation-f.
BibTeX@misc{4ortxyz_comparison-of-tree-based-machine-learning-algorithms-for-predicting-liquefaction-potential-using-canonical-correlation-f_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data}}, year = {2026}, url = {https://4ort.xyz/entity/comparison-of-tree-based-machine-learning-algorithms-for-predicting-liquefaction-potential-using-canonical-correlation-f}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Comparison of tree-based machine learning algorithms for predicting liquefaction potential using canonical correlation forest, rotation forest, and random forest based on CPT data — https://4ort.xyz/entity/comparison-of-tree-based-machine-learning-algorithms-for-predicting-liquefaction-potential-using-canonical-correlation-f (retrieved 2026-05-24)
