Merge pull request automl#1292 from automl/development

Development

CITATION.cff

@@ -0,0 +1,109 @@
+---
+cff-version: 1.2.0
+
+message: "If you use auto-sklearn in a scientific publication, we would appreciate a reference to the following paper"
+
+title: "auto-sklearn"
+date-released: "2015-07-02"
+
+url: "https://automl.github.io/auto-sklearn/master/"
+repository-code: "https://github.com/automl/auto-sklearn"
+
+version: "0.14.0"
+
+type: "software"
+keywords:
+  - "automated machine learning"
+  - "machine learning"
+
+license: "BSD-3-Clause"
+
+authors:
+  - family-names: "Feurer"
+    given-names: "Matthias"
+    orcid: "https://orcid.org/0000-0001-9611-8588"
+    affiliation: "University of Freiburg, Germany"
+
+  - family-names: "Eggensperger"
+    given-names: "Katharina" 
+    orcid: "https://orcid.org/0000-0002-0309-401X"
+    affiliation: "University of Freiburg, Germany"
+
+  - family-name: "Bergman"
+    given-names: "Edward"
+    affiliation: "University of Freiburg, Germany"
+
+  - family-name: "Rivera Valverde"
+    given-names: "Francisco"
+    affiliation: "University of Freiburg, Germany"
+
+  - family-names: "Jost"
+    given-names: "Springenberg"
+    orcid: "https://orcid.org/0000-0002-9392-1006"
+    affiliation: "University of Freiburg, Germany"
+
+  - family-names: "Manuel"
+    given-names: "Blum"
+    affiliation: "University of Freiburg, Germany"
+
+  - family-names: "Hutter"
+    given-names: "Frank"
+    affiliation: "University of Freiburg, Germany"
+
+preferred-citation:
+  type: "proceedings"
+  title: "Efficient and Robust Automated Machine Learning"
+  collection-title: "Advances in Nerual Infromation Processing Systems 28 (2015)"
+  year: 2015
+  pages: "2962--2970"
+  url: "https://papers.neurips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf"
+
+  publisher:
+    name: "Curran Associates, Inc."
+
+  editors:
+
+    - family-names: "Cortes"
+      given-names: "C."
+
+    - family-names: "Lawrence"
+      given-names: "N."
+
+    - family-names: "Lee"
+      given-names: "D."
+
+    - family-names: "Sugiyama"
+      given-names: "M."
+
+    - family-names: "Garnett"
+      given-names: "R."
+
+  authors:
+
+    - family-names: "Feurer"
+      given-names: "Matthias" 
+      orcid: "https://orcid.org/0000-0001-9611-8588"
+      affiliation: "University of Freiburg, Germany"
+
+    - family-names: "Klein"
+      given-names: "Aaron"
+      affiliation: "University of Freiburg, Germany"
+
+    - family-names: "Eggensperger"
+      given-names: "Katharina" 
+      orcid: "https://orcid.org/0000-0002-0309-401X"
+      affiliation: "University of Freiburg, Germany"
+
+    - family-names: "Jost"
+      given-names: "Springenberg"
+      orcid: "https://orcid.org/0000-0002-9392-1006"
+      affiliation: "University of Freiburg, Germany"
+
+    - family-names: "Manuel"
+      given-names: "Blum"
+      affiliation: "University of Freiburg, Germany"
+
+    - family-names: "Hutter"
+      given-names: "Frank"
+      affiliation: "University of Freiburg, Germany"
+...

README.md

@@ -30,14 +30,14 @@ If you use auto-sklearn in scientific publications, we would appreciate citation
 *Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum and Frank Hutter*  
 Advances in Neural Information Processing Systems 28 (2015)  
 
-[Link](https://papers.nips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf) to publication.
+[Link](https://papers.neurips.cc/paper/5872-efficient-and-robust-automated-machine-learning.pdf) to publication.
 ```
 @inproceedings{feurer-neurips15a,
-  title     = {Efficient and Robust Automated Machine Learning},
-  author    = {Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum and Frank Hutter},
-  booktitle = {Advances in Neural Information Processing Systems 28 (2015)},
-  pages     = {2962--2970},
-  year      = {2015}
+    title     = {Efficient and Robust Automated Machine Learning},
+    author    = {Feurer, Matthias and Klein, Aaron and Eggensperger, Katharina  Springenberg, Jost and Blum, Manuel and Hutter, Frank},
+    booktitle = {Advances in Neural Information Processing Systems 28 (2015)},
+    pages     = {2962--2970},
+    year      = {2015}
 }
 ```
 
@@ -49,11 +49,11 @@ arXiv:2007.04074 [cs.LG], 2020
 
 [Link](https://arxiv.org/abs/2007.04074) to publication.
 ```
-@inproceedings{feurer-arxiv20a,
-  title     = {Auto-Sklearn 2.0: The Next Generation},
-  author    = {Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer and Frank Hutter},
-  booktitle = {arXiv:2007.04074 [cs.LG]},
-  year      = {2020}
+@article{feurer-arxiv20a,
+    title     = {Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning},
+    author    = {Feurer, Matthias and Eggensperger, Katharina and Falkner, Stefan and Lindauer, Marius and Hutter, Frank},
+    booktitle = {arXiv:2007.04074 [cs.LG]},
+    year      = {2020}
 }
 ```
 

autosklearn/__version__.py

@@ -1,4 +1,4 @@
 """Version information."""
 
 # The following line *must* be the last in the module, exactly as formatted:
-__version__ = "0.14.0"
+__version__ = "0.14.1"

autosklearn/automl.py

@@ -587,6 +587,7 @@ def fit(
 
         # AutoSklearn does not handle sparse y for now
         y = convert_if_sparse(y)
+        y_test = convert_if_sparse(y_test) if y_test is not None else None
 
         # Get the task if it doesn't exist
         if task is None:

autosklearn/estimators.py

@@ -2,7 +2,7 @@
 from typing import Optional, Dict, List, Tuple, Union, Iterable
 from typing_extensions import Literal
 
-from ConfigSpace.configuration_space import Configuration
+from ConfigSpace.configuration_space import Configuration, ConfigurationSpace
 import dask.distributed
 import joblib
 import numpy as np
@@ -186,7 +186,7 @@ def __init__(
 
         smac_scenario_args : dict, optional (None)
             Additional arguments inserted into the scenario of SMAC. See the
-            `SMAC documentation <https://automl.github.io/SMAC3/master/options.html?highlight=scenario#scenario>`_
+            `SMAC documentation <https://automl.github.io/SMAC3/master/pages/details/scenario.html>`_
             for a list of available arguments.
 
         get_smac_object_callback : callable
@@ -830,7 +830,7 @@ def get_configuration_space(
         y_test: Optional[Union[SUPPORTED_TARGET_TYPES, spmatrix]] = None,
         dataset_name: Optional[str] = None,
         feat_type: Optional[List[str]] = None,
-    ):
+    ) -> ConfigurationSpace:
         """
         Returns the Configuration Space object, from which Auto-Sklearn
         will sample configurations and build pipelines.
@@ -851,6 +851,7 @@ def get_configuration_space(
         """
         if self.automl_ is None:
             self.automl_ = self.build_automl()
+
         return self.automl_.fit(
             X, y,
             X_test=X_test, y_test=y_test,

autosklearn/experimental/askl2.py

@@ -279,9 +279,7 @@ def __init__(
 
         smac_scenario_args : dict, optional (None)
             Additional arguments inserted into the scenario of SMAC. See the
-            `SMAC documentation
-            <https://automl.github.io/SMAC3/master/options.html?highlight=scenario
-            #scenario>`_
+            `SMAC documentation <https://automl.github.io/SMAC3/master/pages/details/scenario.html>`_
             for a list of available arguments.
 
         logging_config : dict, optional (None)

autosklearn/pipeline/components/classification/__init__.py

@@ -1,6 +1,7 @@
 __author__ = 'feurerm'
 
 from collections import OrderedDict
+from typing import Type
 import os
 
 from ..base import AutoSklearnClassificationAlgorithm, find_components, \
@@ -15,7 +16,7 @@
 _addons = ThirdPartyComponents(AutoSklearnClassificationAlgorithm)
 
 
-def add_classifier(classifier):
+def add_classifier(classifier: Type[AutoSklearnClassificationAlgorithm]) -> None:
     _addons.add_component(classifier)
 
 

autosklearn/pipeline/components/data_preprocessing/__init__.py

@@ -1,6 +1,6 @@
 import os
 from collections import OrderedDict
-from typing import Dict, Optional
+from typing import Dict, Optional, Type
 
 from ConfigSpace.configuration_space import ConfigurationSpace
 from ConfigSpace.hyperparameters import CategoricalHyperparameter
@@ -16,7 +16,7 @@
 _addons = ThirdPartyComponents(AutoSklearnPreprocessingAlgorithm)
 
 
-def add_preprocessor(preprocessor: AutoSklearnPreprocessingAlgorithm) -> None:
+def add_preprocessor(preprocessor: Type[AutoSklearnPreprocessingAlgorithm]) -> None:
     _addons.add_component(preprocessor)
 
 

autosklearn/pipeline/components/feature_preprocessing/__init__.py

@@ -1,5 +1,6 @@
-from collections import OrderedDict
 import os
+from collections import OrderedDict
+from typing import Type
 
 from ..base import AutoSklearnPreprocessingAlgorithm, find_components, \
     ThirdPartyComponents, AutoSklearnChoice
@@ -13,7 +14,7 @@
 _addons = ThirdPartyComponents(AutoSklearnPreprocessingAlgorithm)
 
 
-def add_preprocessor(preprocessor):
+def add_preprocessor(preprocessor: Type[AutoSklearnPreprocessingAlgorithm]) -> None:
     _addons.add_component(preprocessor)
 
 

autosklearn/pipeline/components/regression/__init__.py

@@ -1,4 +1,5 @@
 from collections import OrderedDict
+from typing import Type
 import os
 
 from ..base import AutoSklearnRegressionAlgorithm, find_components, \
@@ -13,7 +14,7 @@
 _addons = ThirdPartyComponents(AutoSklearnRegressionAlgorithm)
 
 
-def add_regressor(regressor):
+def add_regressor(regressor: Type[AutoSklearnRegressionAlgorithm]) -> None:
     _addons.add_component(regressor)
 
 

doc/extending.rst

@@ -48,8 +48,7 @@ the type of component:
 get_hyperparameter_search_space()
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-Return an instance of ``HPOlibConfigSpace.configuration_space
-.ConfigurationSpace``.
+Return an instance of ``ConfigSpace.configuration_space.ConfigurationSpace``.
 
 See also the abstract definitions:
 :meth:`AutoSklearnClassificationAlgorithm.get_hyperparameter_search_space() <autosklearn.pipeline.components.base.AutoSklearnClassificationAlgorithm.get_hyperparameter_search_space>`