6 Publikationen

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[6]
2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2939517
Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information
Pfannschmidt, Lukas, Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information. Neurocomputing (). , 2020
PUB | DOI | Download (ext.) | arXiv
 
[5]
2020 | Preprint | Entwurf | PUB-ID: 2942271 OA
Sequential Feature Classification in the Context of Redundancies
Pfannschmidt, Lukas, Sequential Feature Classification in the Context of Redundancies. (). , 2020
PUB | PDF | arXiv
 
[4]
2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2933893
Feature Relevance Bounds for Ordinal Regression
Pfannschmidt, Lukas, Feature Relevance Bounds for Ordinal Regression. Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019) (). Louvain-la-Neuve, 2019
PUB | Download (ext.) | arXiv
 
[3]
2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2935456 OA
FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration
Pfannschmidt, Lukas, FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration. (). , 2019
PUB | PDF | DOI | arXiv
 
[2]
2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2915273 OA
Interpretation of Linear Classifiers by Means of Feature Relevance Bounds
Göpfert, Christina, Interpretation of Linear Classifiers by Means of Feature Relevance Bounds. Neurocomputing 298 (). , 2018
PUB | PDF | DOI | WoS
 
[1]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2908201 OA
Feature Relevance Bounds for Linear Classification
Göpfert, Christina, Feature Relevance Bounds for Linear Classification. Proceedings of the ESANN, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (). Louvain-la-Neuve, 2017
PUB | Dateien verfügbar | Download (ext.)
 

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6 Publikationen

Alle markieren

[6]
2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2939517
Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information
Pfannschmidt, Lukas, Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information. Neurocomputing (). , 2020
PUB | DOI | Download (ext.) | arXiv
 
[5]
2020 | Preprint | Entwurf | PUB-ID: 2942271 OA
Sequential Feature Classification in the Context of Redundancies
Pfannschmidt, Lukas, Sequential Feature Classification in the Context of Redundancies. (). , 2020
PUB | PDF | arXiv
 
[4]
2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2933893
Feature Relevance Bounds for Ordinal Regression
Pfannschmidt, Lukas, Feature Relevance Bounds for Ordinal Regression. Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019) (). Louvain-la-Neuve, 2019
PUB | Download (ext.) | arXiv
 
[3]
2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2935456 OA
FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration
Pfannschmidt, Lukas, FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration. (). , 2019
PUB | PDF | DOI | arXiv
 
[2]
2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2915273 OA
Interpretation of Linear Classifiers by Means of Feature Relevance Bounds
Göpfert, Christina, Interpretation of Linear Classifiers by Means of Feature Relevance Bounds. Neurocomputing 298 (). , 2018
PUB | PDF | DOI | WoS
 
[1]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2908201 OA
Feature Relevance Bounds for Linear Classification
Göpfert, Christina, Feature Relevance Bounds for Linear Classification. Proceedings of the ESANN, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (). Louvain-la-Neuve, 2017
PUB | Dateien verfügbar | Download (ext.)
 

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