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EXPLAINING KERNEL CLUSTERING VIA DECISION TREES
Maximilian Fleissner
, Leena C. Vankadara
,
Debarghya Ghoshdastidar
Informatics 7 - Associate Professorship of Theoretical Foundations of Artificial Intelligence
Technical University of Munich
Amazon Research Tübingen
Research output
:
Contribution to conference
›
Paper
›
peer-review
3
Scopus citations
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Keyphrases
Approximation Guarantee
16%
Clustering Methods
33%
Decision Tree
100%
Explainable Machine Learning
16%
Flexible Clustering
16%
Interpretable Clustering
16%
Interpretable Machine Learning
16%
K-means
100%
Kernel Clustering
100%
Model Interpretation
16%
Nonlinear Extensions
16%
Computer Science
Approximation (Algorithm)
33%
Clustering Method
66%
Decision Tree
100%
Efficient Algorithm
33%
Explainable Artificial Intelligence
33%
Interpretability
33%
Interpretable Machine Learning
33%
Mean Algorithm
33%