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Summary
DescriptionHyperparameter Optimization using Tree-Structured Parzen Estimators.svg
Deutsch: Bei der Hyperparameteroptimierung mit Tree-Structured Parzen Estimators (TPE) wird ein Modell über die Beziehung zwischen Hyperparametern und gemessener Performance des zu optimierenden Maschinelles-Lernen-Modells angelegt, um Bereiche mit einer guten Performance näher zu untersuchen und weiterhin andere Bereiche des Suchraums zu explorieren. Wie das Beispiel zeigt, befinden sich die meisten der 100 Versuche in der Nähe der tatsächlich besten Performance (blau). Im Gegensatz zur Raster- und zur Zufallssuche wird das Optimum wesentlich genauer gefunden und eine vergleichbare Performance in weniger Versuchen erreicht.
English: In hyperparameter optimization with tree-structured Parzen estimators (TPE), the optimizer creates a model of the relation between hyperparameters and measured performance of the machine learning model to optimize. Areas of the search space with a better performance are searched more likely. At the same time, other areas are further explored. The example shows that most of the 100 trials are close to the optimum (better performance = blue). In contrast to grid search and random search, better hyperparameter values are found in fewer trials.
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