Titlebook: Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and ; Proceedings of the 1 Thomas Villmann,

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Gruppenarbeit in der industriellen Praxis,st validate the proposed curves on artificial benchmark data against the ARC as a baseline. We then show on benchmarks and medical, real-world data with class imbalances that the proposed precision- and recall-curves yield more accurate insights into classifier performance than ARCs.

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Outmoded

,New Cloth Unto an Old Garment: SOM for Regeneration Learning, cross-modal representations in a topologically coherent map. This approach enables bidirectional predictive/regenerative mapping between domains. We evaluate the potential of this method for an unsolved (so far!) practical problem in petroleum geoscience.

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