Merge pull request #1083 from automl/development

Release 0.12.3

Author: mfeurer

.landscape.yaml

@@ -18,6 +18,10 @@ repos:
         args: [--show-error-codes]
         name: mypy auto-sklearn-util
         files: autosklearn/util
+      - id: mypy
+        args: [--show-error-codes]
+        name: mypy auto-sklearn-evaluation
+        files: autosklearn/evaluation
   - repo: https://gitlab.com/pycqa/flake8
     rev: 3.8.3
     hooks:

.pre-commit-config.yaml

@@ -24,17 +24,3 @@ Auto-Sklearn 2.0: The Next Generation
 Authors: Matthias Feurer, Katharina Eggensperger, Stefan Falkner, Marius Lindauer and Frank Hutter  
 arXiv:2007.04074 [cs.LG], 2020
 https://arxiv.org/abs/2007.04074
-
-## Status
-
-Status for master branch
-
-[![Build Status](https://travis-ci.org/automl/auto-sklearn.svg?branch=master)](https://travis-ci.org/automl/auto-sklearn)
-[![Code Health](https://landscape.io/github/automl/auto-sklearn/master/landscape.png)](https://landscape.io/github/automl/auto-sklearn/master)
-[![codecov](https://codecov.io/gh/automl/auto-sklearn/branch/master/graph/badge.svg)](https://codecov.io/gh/automl/auto-sklearn)
-
-Status for development branch
-
-[![Build Status](https://travis-ci.org/automl/auto-sklearn.svg?branch=development)](https://travis-ci.org/automl/auto-sklearn)
-[![Code Health](https://landscape.io/github/automl/auto-sklearn/development/landscape.png)](https://landscape.io/github/automl/auto-sklearn/development)
-[![codecov](https://codecov.io/gh/automl/auto-sklearn/branch/development/graph/badge.svg)](https://codecov.io/gh/automl/auto-sklearn)

README.md

@@ -1,4 +1,4 @@
 """Version information."""
 
 # The following line *must* be the last in the module, exactly as formatted:
-__version__ = "0.12.2"
+__version__ = "0.12.3"

autosklearn/__version__.py

@@ -1268,8 +1268,8 @@ def cv_results_(self):
 
         results['mean_fit_time'] = np.array(mean_fit_time)
         results['params'] = params
-        results['rank_test_scores'] = scipy.stats.rankdata(1 - results['mean_test_score'],
-                                                           method='min')
+        rank_order = -1 * self._metric._sign * results['mean_test_score']
+        results['rank_test_scores'] = scipy.stats.rankdata(rank_order, method='min')
         results['status'] = status
         results['budgets'] = budgets
 

autosklearn/automl.py

@@ -386,3 +386,20 @@ def _check_data(
                                  self.type_of_target,
                                  supported_output_types
                              ))
+
+    @property
+    def classes_(self) -> np.ndarray:
+        """
+        Complies with scikit learn classes_ attribute,
+        which consist of a ndarray of shape (n_classes,)
+        where n_classes are the number of classes seen while fitting
+        a encoder to the targets.
+        Returns
+        -------
+            classes_: np.ndarray
+                The unique classes seen during encoding of a classifier
+        """
+        if self.encoder is None:
+            return np.array([])
+        else:
+            return self.encoder.categories_[0]