Closed psinger closed 7 years ago
Hi! It is straightforward to use another loss function. For example, when using a scikit-learn compatible classifier, see this: https://github.com/zygmuntz/hyperband/blob/master/common_defs.py#L63
You could also modify that very function to use cross-validation.
Thanks, already figured it out :)
Hi! I am wondering whether it is possible to optimize with cross validation and preferably with a custom scoring function. Currently, it picks the configuration that minimizes e.g., the log loss of the training data if I am not mistaken. Would be good to also have similar options as grid search offers in scikit learn.