DescriptionHyperparameter Optimization using Grid Search.svg
Deutsch: Für beide Hyperparameter eines Modells wird eine diskrete Menge von Werten festgelegt (hier jeweils 10 Elemente). Bei der Hyperparameteroptimierung mit Rastersuche werden nacheinander Modelle für alle Kombinationen der Werte ausprobiert und die Performance gemessen (gute Performance = blau, schlechte Performance = rot). Im Beispiel gibt es somit insgesamt 100 Versuche. Das Modell mit der besten Performance wird abschließend ausgewählt.
English: For both hyperparameters of a model, a discrete set of values to search is defined (here, 10 values). In hyperparameter optimization with grid search, the model is trained using each combination of hyperparameter values (100 trials in this example) and the model performance (colored lines, better performance = blue) is saved. Finally, the model with the best performance is selected.
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