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Oliver Urs Lenz
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2020 – today
- 2024
- [j5]Oliver Urs Lenz
, Daniel Peralta
, Chris Cornelis
:
Polar Encoding: A Simple Baseline Approach for Classification With Missing Values. IEEE Trans. Fuzzy Syst. 32(5): 3084-3093 (2024) - 2023
- [c5]Oliver Urs Lenz
, Chris Cornelis
:
Classifying Token Frequencies Using Angular Minkowski p-Distance. IJCRS 2023: 402-413 - [e1]Andrea Campagner, Oliver Urs Lenz, Shuyin Xia, Dominik Slezak
, Jaroslaw Was
, JingTao Yao:
Rough Sets - International Joint Conference, IJCRS 2023, Krakow, Poland, October 5-8, 2023, Proceedings. Lecture Notes in Computer Science 14481, Springer 2023, ISBN 978-3-031-50958-2 [contents] - [i7]Oliver Urs Lenz, Chris Cornelis:
Classifying token frequencies using angular Minkowski p-distance. CoRR abs/2309.14495 (2023) - [i6]Oliver Urs Lenz, Henri Bollaert, Chris Cornelis:
A unified weighting framework for evaluating nearest neighbour classification. CoRR abs/2311.16872 (2023) - 2022
- [j4]Adnan Theerens
, Oliver Urs Lenz
, Chris Cornelis
:
Choquet-based fuzzy rough sets. Int. J. Approx. Reason. 146: 62-78 (2022) - [j3]Oliver Urs Lenz
, Daniel Peralta
, Chris Cornelis
:
Optimised one-class classification performance. Mach. Learn. 111(8): 2863-2883 (2022) - [c4]Oliver Urs Lenz, Chris Cornelis, Daniel Peralta:
Fuzzy-rough-learn 0.2: a Python library for fuzzy rough set algorithms and one-class classification. FUZZ-IEEE 2022: 1-8 - [i5]Adnan Theerens, Oliver Urs Lenz, Chris Cornelis:
Choquet-Based Fuzzy Rough Sets. CoRR abs/2202.10872 (2022) - [i4]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
No imputation without representation. CoRR abs/2206.14254 (2022) - [i3]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Representing missing values through polar encoding. CoRR abs/2210.01905 (2022) - 2021
- [j2]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis
:
Average Localised Proximity: A new data descriptor with good default one-class classification performance. Pattern Recognit. 118: 107991 (2021) - [c3]Oliver Urs Lenz
, Daniel Peralta
, Chris Cornelis
:
Adapting Fuzzy Rough Sets for Classification with Missing Values. IJCRS 2021: 192-200 - [i2]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Average Localised Proximity: a new data descriptor with good default one-class classification performance. CoRR abs/2101.11037 (2021) - [i1]Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Optimised one-class classification performance. CoRR abs/2102.02618 (2021) - 2020
- [j1]Oliver Urs Lenz
, Daniel Peralta
, Chris Cornelis
:
Scalable Approximate FRNN-OWA Classification. IEEE Trans. Fuzzy Syst. 28(5): 929-938 (2020) - [c2]Oliver Urs Lenz
, Daniel Peralta
, Chris Cornelis
:
fuzzy-rough-learn 0.1: A Python Library for Machine Learning with Fuzzy Rough Sets. IJCRS 2020: 491-499
2010 – 2019
- 2019
- [c1]Oliver Urs Lenz
, Daniel Peralta
, Chris Cornelis
:
A Scalable Approach to Fuzzy Rough Nearest Neighbour Classification with Ordered Weighted Averaging Operators. IJCRS 2019: 197-209
Coauthor Index
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last updated on 2024-05-19 01:02 CEST by the dblp team
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