Scripts and notebooks to reproduce the experiments and analyses of the paper Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm, "Efficient SVDD sampling with approximation guarantees for the decision boundary", Machine Learning (2022).
machine-learning
data-reduction
classification
outlier-detection
anomaly-detection
one-class
svdd
support-vector-data-description
sampling-strategies
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Updated
Apr 14, 2022 - Jupyter Notebook