Kreuzvalidierungsverfahren (German Wikipedia)

Analysis of information sources in references of the Wikipedia article "Kreuzvalidierungsverfahren" in German language version.

refsWebsite

Global rank German rank

2zdb-katalog.de

123^rd place

6^th place

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low place

low place

2,020^th place

3,598^th place

69^th place

189^th place

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961^st place

1,564^th place

3,084^th place

arxiv.org

Sterling G. Baird, Marianne Liu, Hasan M. Sayeed, Taylor D. Sparks: Data-Driven Materials Discovery and Synthesis using Machine Learning Methods. 28. Februar 2022, arxiv:2202.02380v2.

cmu.edu

cs.cmu.edu

https://www.cs.cmu.edu/~schneide/tut5/node42.html

doi.org

Bryce Meredig, Erin Antono, Carena Church, Maxwell Hutchinson, Julia Ling: Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery. In: Molecular Systems Design & Engineering. Band 3, Nr. 5, 2018, ISSN 2058-9689, S. 819–825, doi:10.1039/C8ME00012C (rsc.org [abgerufen am 15. Juni 2022]).
Steven K. Kauwe, Jake Graser, Antonio Vazquez, Taylor D. Sparks: Machine Learning Prediction of Heat Capacity for Solid Inorganics. In: Integrating Materials and Manufacturing Innovation. Band 7, Nr. 2, 1. Juni 2018, ISSN 2193-9772, S. 43–51, doi:10.1007/s40192-018-0108-9.

psu.edu

citeseerx.ist.psu.edu

Cantzler, H. "Random sample consensus (ransac)." Institute for Perception, Action and Behaviour, Division of Informatics, University of Edinburgh (1981). http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.106.3035&rep=rep1&type=pdf

rsc.org

xlink.rsc.org

Bryce Meredig, Erin Antono, Carena Church, Maxwell Hutchinson, Julia Ling: Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery. In: Molecular Systems Design & Engineering. Band 3, Nr. 5, 2018, ISSN 2058-9689, S. 819–825, doi:10.1039/C8ME00012C (rsc.org [abgerufen am 15. Juni 2022]).

waikato.ac.nz

cs.waikato.ac.nz

Ian H. Witten, Eibe Frank und Mark A. Hall: Data Mining: Practical Machine Learning Tools and Techniques. 3. Auflage. Morgan Kaufmann, Burlington, MA 2011, ISBN 978-0-12-374856-0 (waikato.ac.nz).

zdb-katalog.de

Bryce Meredig, Erin Antono, Carena Church, Maxwell Hutchinson, Julia Ling: Can machine learning identify the next high-temperature superconductor? Examining extrapolation performance for materials discovery. In: Molecular Systems Design & Engineering. Band 3, Nr. 5, 2018, ISSN 2058-9689, S. 819–825, doi:10.1039/C8ME00012C (rsc.org [abgerufen am 15. Juni 2022]).
Steven K. Kauwe, Jake Graser, Antonio Vazquez, Taylor D. Sparks: Machine Learning Prediction of Heat Capacity for Solid Inorganics. In: Integrating Materials and Manufacturing Innovation. Band 7, Nr. 2, 1. Juni 2018, ISSN 2193-9772, S. 43–51, doi:10.1007/s40192-018-0108-9.