Hyperparameter_Optimization_using_Random_Search.svg
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Summary
| Description |
Deutsch:
Bei der Hyperparameteroptimierung mit Zufallssuche werden Modelle mit zufällig aus einem Suchraum gezogenen Hyperparameterwerten trainiert. Die Modellperformance in Abhängigkeit zu den Hyperparametern (gute Performance = blau, schlechte Performance = rot) beeinflusst die Auswahl nicht. Das Modell mit der besten Performance wird abschließend ausgewählt. Im Beispiel fanden 100 Versuche statt. Bezogen auf einen einzelnen Hyperparameter werden im Gegensatz zur Rastersuche wesentlich mehr Werte ausprobiert (grüne Striche).
English:
In hyperparameter optimization with random search, the model is trained with randomly chosen hyperparameter values. The performance in relation to hyperparameters (colored lines, better performance = blue) does not influence the choice of trials. Finally, the model with the best performance is selected. In this example, 100 trials were run. Looking at a single hyperparameter, much more different values were tried in contrast to grid search (green lines).
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| Date | |
| Source | Own work |
| Author | Alexander Elvers |
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