A refined approach for evaluating small datasets via binary classification using machine learning

Steffen Steinert; Verena Ruf; David Dzsotjan; Nicolas Großmann; Albrecht Schmidt; Jochen Kuhn; Stefan Küchemann

doi:10.1371/journal.pone.0301276

Loading metrics

Open Access

Peer-reviewed

Research Article

A refined approach for evaluating small datasets via binary classification using machine learning

Steffen Steinert ,

Roles Conceptualization, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft

* E-mail: steinert.steffen@physik.uni-muenchen.de

Affiliations Chair of Physics Education, Ludwig-Maximilians-Universität München (LMU Munich), Munich, Germany, Department of Electrical and Computer Engineering, RPTU Kaiserslautern-Landau, Germany

https://orcid.org/0000-0001-6364-934X

⨯
Verena Ruf,

Roles Investigation, Writing – review & editing

Affiliation Chair of Physics Education, Ludwig-Maximilians-Universität München (LMU Munich), Munich, Germany

https://orcid.org/0000-0002-9762-7621

⨯
David Dzsotjan,

Roles Investigation, Writing – review & editing

Affiliation Chair of Physics Education, Ludwig-Maximilians-Universität München (LMU Munich), Munich, Germany
⨯
Nicolas Großmann,

Roles Investigation, Writing – review & editing

Affiliation Smart Data & Knowledge Services, German Research Center for Artificial Intelligence, Kaiserslautern, Germany
⨯
Albrecht Schmidt,

Roles Investigation, Supervision, Writing – review & editing

Affiliation Human-Centered Ubiquitous Media, Ludwig-Maximilians-Universität München (LMU Munich), Munich, Germany
⨯
Jochen Kuhn,

Roles Investigation, Supervision, Writing – review & editing

Affiliation Chair of Physics Education, Ludwig-Maximilians-Universität München (LMU Munich), Munich, Germany

https://orcid.org/0000-0002-6985-3218

⨯
Stefan Küchemann

Roles Conceptualization, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing

Affiliation Chair of Physics Education, Ludwig-Maximilians-Universität München (LMU Munich), Munich, Germany

https://orcid.org/0000-0003-2729-1592

⨯

A refined approach for evaluating small datasets via binary classification using machine learning

Steffen Steinert,
Verena Ruf,
David Dzsotjan,
Nicolas Großmann,
Albrecht Schmidt,
Jochen Kuhn,
Stefan Küchemann

Published: May 21, 2024
https://doi.org/10.1371/journal.pone.0301276

Reader Comments (0)

Post a new comment on this article

Subject Areas
?

For more information about PLOS Subject Areas, click here.
We want your feedback. Do these Subject Areas make sense for this article? Click the target next to the incorrect Subject Area and let us know. Thanks for your help!

Permutation
Is the Subject Area "Permutation" applicable to this article?

Thanks for your feedback.
Statistical data
Is the Subject Area "Statistical data" applicable to this article?

Thanks for your feedback.
Machine learning
Is the Subject Area "Machine learning" applicable to this article?

Thanks for your feedback.
Algorithms
Is the Subject Area "Algorithms" applicable to this article?

Thanks for your feedback.
Support vector machines
Is the Subject Area "Support vector machines" applicable to this article?

Thanks for your feedback.
Machine learning algorithms
Is the Subject Area "Machine learning algorithms" applicable to this article?

Thanks for your feedback.
Test statistics
Is the Subject Area "Test statistics" applicable to this article?

Thanks for your feedback.
Probability distribution
Is the Subject Area "Probability distribution" applicable to this article?

Thanks for your feedback.