21
Jun
![Teaser image to Rank-based support vector machines for highly imbalanced data using nominated samples](/images/logos/stat-colloquium.png)
Rank-based support vector machines for highly imbalanced data using nominated samples
Mohammad Jafari Jozani, University of Manitoba, Winnipeg, Canada
21.06.2023
4:15 pm - 5:45 pm
LMU Department of Statistics and via zoom
The talk proposes a novel approach, MaxNS, that tackles highly imbalanced binary classification using expert opinions and rank information. Biasing training samples towards the minority class, it employs rank-based Hinge and Logistic loss functions.
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