Comparison of Machine Learning Methods for Predicting Employee Absences

Abstract:
No abstract specified

SEEK ID: https://publications.h-its.org/publications/1314

DOI: 10.11588/emclpp.2021.02.81078

Research Groups: Data Mining and Uncertainty Quantification

Publication type: Unpublished

Journal: Preprint Series of the Engineering Mathematics and Computing Lab

Citation:

Date Published: 4th May 2021

URL: https://journals.ub.uni-heidelberg.de/index.php/emcl-pp/article/view/81078

Registered Mode: manually

Authors: Alejandra Jayme, Philipp Lösel, Vincent Heuveline

help Submitter
Citation
Jayme, A., Lösel, P. D., Fischer, J., & Heuveline, V. (2021). Comparison of Machine Learning Methods for Predicting Employee Absences. Preprint Series of the Engineering Mathematics and Computing Lab, Nr. 02 (2021): Comparison of Machine Learning Methods for Predicting Employee Absences. https://doi.org/10.11588/EMCLPP.2021.02.81078
Activity

Views: 3299

Created: 15th Nov 2021 at 09:43

Last updated: 5th Mar 2024 at 21:24

help Tags

This item has not yet been tagged.

help Attributions

None

Powered by
(v.1.14.2)
Copyright © 2008 - 2023 The University of Manchester and HITS gGmbH