auto-sklearn
auto-sklearn copied to clipboard
automl
Automated Machine Learning with scikit-learn
Scikit-learn's model selection modules such as [RandomizedSearchCV](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html#sklearn.model_selection.RandomizedSearchCV) and [HalvingRandomSearchCV](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.HalvingRandomSearchCV.html#sklearn.model_selection.HalvingRandomSearchCV) use the feature name `scoring` instead of `metric`. We should follow scikit-learn here and deprecate the argument `metric` and replace it...
As part of statistics on the search procedure.
The current API, the [Auto-sklearn 2.0 paper](https://arxiv.org/abs/2007.04074) nomenclature and scikit-learn nomencature are different: | current API | Auto-sklearn 2.0 terminology | sklearn | should be named | |---|---|---|---| | `resampling_strategy`...
We reduce the precision for `fit` if it's required so the models are trained on a reduced precision, e.g. `np.float128` to `np.float64`. We also subsample if the dataset is still...
# Short Question Description Hello, thanks for developing autosklearn! I'm trying it and I have a question. I would like to ask if autosklearn supports to resume training from a...
Hi! I'm experiencing a problem when I fit an AutoSklearn instance in a virtual machine with many cores. I have run exactly the same code, with the same dataset in...
Currently, configuring the logger is incredibly hard: * It is unclear which loggers can be configured at all * There is an example, but it is hard to adapt It...
I'm trying to find out the metrics for my multi-label classification Iris dataset, and I'm getting a "NaN" for precision, recall, f1, and roc_auc. Below is my code: ```python automl...
For example, I have a XGB model, the prediction is not too bad. I plan to use it as a baseline model, and use it's hyperparams as the initial value...
