Home ›
Entities
› academia
› Evaluating explorative prediction power of machine learning algorithms for materials discovery using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"> <mml:mrow> <mml:mi>k</mml:mi> </mml:mrow> </mml:math> -fold forward cross-validation
Evaluating explorative prediction power of machine learning algorithms for materials discovery using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"> <mml:mrow> <mml:mi>k</mml:mi> </mml:mrow> </mml:math> -fold forward cross-validation
Evaluating explorative prediction power of machine learning algorithms for materials discovery using k -fold forward cross-validation
Summary
Evaluating explorative prediction power of machine learning algorithms for materials discovery using k -fold forward cross-validation is a scholarly article<sup id="cite-A2" class="cite-ref" title="Evaluating explorative prediction power of machine learning algorithms for materials discovery using k[1].
Key Facts
Evaluating explorative prediction power of machine learning algorithms for materials discovery using k -fold forward cross-validation's instance of is recorded as scholarly article<sup id="cite-C1" class="cite-ref" title="Evaluating explorative prediction power of machine learning algorithms for materials discovery using k[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). Evaluating explorative prediction power of machine learning algorithms for materials discovery using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"> <mml:mrow> <mml:mi>k</mml:mi> </mml:mrow> </mml:math> -fold forward cross-validation. Retrieved May 24, 2026, from https://4ort.xyz/entity/evaluating-explorative-prediction-power-of-machine-learning-algorithms-for-materials-discovery-using-mml-math-xmlns-mml-
MLA“Evaluating explorative prediction power of machine learning algorithms for materials discovery using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"> <mml:mrow> <mml:mi>k</mml:mi> </mml:mrow> </mml:math> -fold forward cross-validation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/evaluating-explorative-prediction-power-of-machine-learning-algorithms-for-materials-discovery-using-mml-math-xmlns-mml-.
BibTeX@misc{4ortxyz_evaluating-explorative-prediction-power-of-machine-learning-algorithms-for-materials-discovery-using-mml-math-xmlns-mml-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Evaluating explorative prediction power of machine learning algorithms for materials discovery using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"> <mml:mrow> <mml:mi>k</mml:mi> </mml:mrow> </mml:math> -fold forward cross-validation}}, year = {2026}, url = {https://4ort.xyz/entity/evaluating-explorative-prediction-power-of-machine-learning-algorithms-for-materials-discovery-using-mml-math-xmlns-mml-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Evaluating explorative prediction power of machine learning algorithms for materials discovery using <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"> <mml:mrow> <mml:mi>k</mml:mi> </mml:mrow> </mml:math> -fold forward cross-validation — https://4ort.xyz/entity/evaluating-explorative-prediction-power-of-machine-learning-algorithms-for-materials-discovery-using-mml-math-xmlns-mml- (retrieved 2026-05-24)
