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10 Publikationen

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[10]
2023 | Diskussionspapier | FH-PUB-ID: 3731 | OA
Active Learning mit dem GUIDE-Entscheidungsbaum
J. Kösters, M. Schöne, Active Learning mit dem GUIDE-Entscheidungsbaum, n.d.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[9]
2023 | Diskussionspapier | FH-PUB-ID: 3729 | OA
Benchmarking of Machine Learning Models for Tabular Scarce Data
J. Kösters, M. Schöne, M. Kohlhase, Benchmarking of Machine Learning Models for Tabular Scarce Data, n.d.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[8]
2022 | Konferenzbeitrag | FH-PUB-ID: 2232
Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, M. Kuhn, in: H. Yin, D. Camacho, P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, Springer International Publishing, Cham, 2022, pp. 379–390.
HSBI-PUB | DOI
 
[7]
2022 | Buchbeitrag | FH-PUB-ID: 2291 | OA
Analysis of the Behavior of Online Decision Trees Under Concept Drift at the Example of FIMT-DD
M. Hanitz, M. Schöne, T. Voigt, M. Kohlhase, in: P. Perner (Ed.), Machine Learning and Data Mining in Pattern Recognition, MLDM 2022, ibai-publishing, Leipzig, 2022, pp. 121–135.
HSBI-PUB | Download (ext.)
 
[6]
2021 | Konferenzbeitrag | FH-PUB-ID: 3718
Space-Filling Designs for Experiments with Assembled Products
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, M. Kuhn, in: 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, New York, NY, USA, 2021, pp. 192–199.
HSBI-PUB | DOI | Download (ext.)
 
[5]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Advanced Data Analytics Platform for Manufacturing Companies
T. Voigt, N. Migenda, M. Schöne, D. Pelkmann, M. Fricke, W. Schenck, M. Kohlhase, in: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE, 2021, pp. 01–08.
HSBI-PUB | DOI
 
[4]
2021 | Konferenzbeitrag | FH-PUB-ID: 1912
Curvature-Oriented Splitting for Multivariate Model Trees
M. Schöne, M. Kohlhase, in: 2021 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2021, pp. 01–09.
HSBI-PUB | DOI | Download (ext.)
 
[3]
2021 | Konferenzbeitrag | FH-PUB-ID: 1560 | OA
Assistenzsystem zur Qualitätssicherung von IoT-Geräten basierend auf AutoML und SHAP
J. Ewerszumrode, M. Schöne, S. Godt, M. Kohlhase, in: Proceedings - 31. Workshop Computational Intelligence , KIT Scientific Publishing, 2021, pp. 285–305.
HSBI-PUB | DOI | Download (ext.)
 
[2]
2020 | Buchbeitrag | FH-PUB-ID: 1915 | OA
Least-Squares-Based Construction Algorithm for Oblique and Mixed Regression Trees
M. Schöne, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings -- 30. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2020.
HSBI-PUB | DOI | Download (ext.)
 
[1]
2020 | Buchbeitrag | FH-PUB-ID: 1916
Least Squares Approach for Multivariate Split Selection in Regression Trees
M. Schöne, M. Kohlhase, in: C. Analide, P. Novais, D. Camacho, H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part I, Springer International Publishing, Cham, 2020, pp. 41–50.
HSBI-PUB | DOI | Download (ext.)
 

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10 Publikationen

Alle markieren

[10]
2023 | Diskussionspapier | FH-PUB-ID: 3731 | OA
Active Learning mit dem GUIDE-Entscheidungsbaum
J. Kösters, M. Schöne, Active Learning mit dem GUIDE-Entscheidungsbaum, n.d.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[9]
2023 | Diskussionspapier | FH-PUB-ID: 3729 | OA
Benchmarking of Machine Learning Models for Tabular Scarce Data
J. Kösters, M. Schöne, M. Kohlhase, Benchmarking of Machine Learning Models for Tabular Scarce Data, n.d.
HSBI-PUB | Dateien verfügbar | Download (ext.)
 
[8]
2022 | Konferenzbeitrag | FH-PUB-ID: 2232
Using Design of Experiments to Support the Commissioning of Industrial Assembly Processes
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, M. Kuhn, in: H. Yin, D. Camacho, P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022. 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings, Springer International Publishing, Cham, 2022, pp. 379–390.
HSBI-PUB | DOI
 
[7]
2022 | Buchbeitrag | FH-PUB-ID: 2291 | OA
Analysis of the Behavior of Online Decision Trees Under Concept Drift at the Example of FIMT-DD
M. Hanitz, M. Schöne, T. Voigt, M. Kohlhase, in: P. Perner (Ed.), Machine Learning and Data Mining in Pattern Recognition, MLDM 2022, ibai-publishing, Leipzig, 2022, pp. 121–135.
HSBI-PUB | Download (ext.)
 
[6]
2021 | Konferenzbeitrag | FH-PUB-ID: 3718
Space-Filling Designs for Experiments with Assembled Products
T. Voigt, M. Schöne, M. Kohlhase, O. Nelles, M. Kuhn, in: 2021 3rd International Conference on Management Science and Industrial Engineering, ACM, New York, NY, USA, 2021, pp. 192–199.
HSBI-PUB | DOI | Download (ext.)
 
[5]
2021 | Konferenzbeitrag | FH-PUB-ID: 2571
Advanced Data Analytics Platform for Manufacturing Companies
T. Voigt, N. Migenda, M. Schöne, D. Pelkmann, M. Fricke, W. Schenck, M. Kohlhase, in: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE, 2021, pp. 01–08.
HSBI-PUB | DOI
 
[4]
2021 | Konferenzbeitrag | FH-PUB-ID: 1912
Curvature-Oriented Splitting for Multivariate Model Trees
M. Schöne, M. Kohlhase, in: 2021 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2021, pp. 01–09.
HSBI-PUB | DOI | Download (ext.)
 
[3]
2021 | Konferenzbeitrag | FH-PUB-ID: 1560 | OA
Assistenzsystem zur Qualitätssicherung von IoT-Geräten basierend auf AutoML und SHAP
J. Ewerszumrode, M. Schöne, S. Godt, M. Kohlhase, in: Proceedings - 31. Workshop Computational Intelligence , KIT Scientific Publishing, 2021, pp. 285–305.
HSBI-PUB | DOI | Download (ext.)
 
[2]
2020 | Buchbeitrag | FH-PUB-ID: 1915 | OA
Least-Squares-Based Construction Algorithm for Oblique and Mixed Regression Trees
M. Schöne, M. Kohlhase, in: H. Schulte, F. Hoffmann, R. Mikut (Eds.), Proceedings -- 30. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, 2020.
HSBI-PUB | DOI | Download (ext.)
 
[1]
2020 | Buchbeitrag | FH-PUB-ID: 1916
Least Squares Approach for Multivariate Split Selection in Regression Trees
M. Schöne, M. Kohlhase, in: C. Analide, P. Novais, D. Camacho, H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part I, Springer International Publishing, Cham, 2020, pp. 41–50.
HSBI-PUB | DOI | Download (ext.)
 

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