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Copy file name to clipboardExpand all lines: README.md
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@@ -19,7 +19,7 @@ In the figure, **Data** is provided by user and
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**Portfolio** is a predefined pool of machine learning algorithms, e.g. LightGBM and support vector machine, to solve either
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regression or classification task on the provided dataset.
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Then API starts the following procedures:
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1.**Validate input data**: Process each data type that can be handled by Auto-Pytorch such as encoding categorical data
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1.**Validate input data**: Process each data type, e.g. encoding categorical data, so that Auto-Pytorch can handled
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2.**Create dataset**: Create a dataset that can be handled in this API including cross validation splits
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3.**Evaluate baselines**: Train each algorithm in the predefined pool with a fixed hyperparameter configuration and dummy model from `sklearn.dummy` that represents the worst possible performance
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4.**Search by [SMAC](https://github.com/automl/SMAC3)**:\
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