auto-sklearn
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automl
Automated Machine Learning with scikit-learn
What are the recommeded search space parameters for autosklearn to take maximum benefit from distributed training on multiple CPUs and long time budgets (1day plus)? Context: Most of the available...
Hi, sorry, I am having some problems accessing the validation scores when using Leave-One-Group-Out-Validation. As far as I understood the best validation score (the one that is returned in "sprint_statistics()")...
As per the title, it will be useful for ASKL2 to have a configurable `portfolio` and `policy selector`. It's beneficial for research (avoiding 'cheating' through meta-learning in a benchmark) or...
Auto-sklearn performance might be affected by disk usage. For example, if the disk that hosts the temporal directory where the machine learning models are stored is full (or close to...
Problem statement: scikit learn 0.24 does not support `np.nan` when doing ordinal encoding of categorical columns. This is a feature added in 0.25. Because of this, we are forced to...
We currently only document how to use CV etc., but not how to use the mode from the Auto-WEKA. This should be documented in the respective example: https://automl.github.io/auto-sklearn/master/examples/40_advanced/example_resampling.html#cross-validation
We can improve the testing of automl utils, specifically line [362](https://github.com/automl/auto-sklearn/blob/d2b317c74fb783bde4e55ca8f7b9e4d5c5d236c1/test/test_automl/test_automl.py#L362) when a new release of smac is created that contains https://github.com/automl/SMAC3/pull/712.
Currently I see no support for auto-sklearn to read and write from s3. Providing support for s3 opens up a door in running auto-sklearn pipelines in distributed mode in cloud...
Hi automl-hackers, I feel this package could do some significant progress on the regression front. I can send you some chemistry-related datasets from the real-world, if you are interested. Also,...
to check for compatibility with scikit-learn (https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/utils/estimator_checks.py). From the docs: ```python Check if estimator adheres to scikit-learn conventions. This estimator will run an extensive test-suite for input validation, shapes, etc,...