[MRG] Upgrade to support newest scikit-learn version (#188)

* Upgrade to sklearn==0.20.

* Upgrade to sklearn==0.22.

* Upgrade to sklearn==0.23.

* Upgrade to sklearn==0.24.

* Change the spacing style back to the original ver.

* Pass CI with specific version range of sklearn.

* Change the spacing style back to the original ver.

* Change the spacing style back to the original ver.

* Update libact/query_strategies/multiclass/mdsp.py

Change the import style.

Co-authored-by: yangarbiter <yangarbiter@users.noreply.github.com>

Co-authored-by: yangarbiter <yangarbiter@users.noreply.github.com>

Author: ariapoy

libact/models/tests/test_svm.py

@@ -29,7 +29,7 @@ def setUp(self):
     def test_svm(self):
         svc_clf = SVC(gamma="auto")
         svc_clf.fit(self.X_train, self.y_train)
-        svm = SVM()
+        svm = SVM(gamma="auto")
         svm.train(Dataset(self.X_train, self.y_train))
 
         assert_array_equal(

libact/query_strategies/multiclass/mdsp.py

@@ -16,8 +16,8 @@
 from sklearn.base import BaseEstimator
 from sklearn.metrics import euclidean_distances
 from sklearn.utils import check_random_state, check_array, check_symmetric
-from sklearn.externals.joblib import Parallel
-from sklearn.externals.joblib import delayed
+from joblib import Parallel, delayed
+
 from sklearn.isotonic import IsotonicRegression
 
 

libact/query_strategies/multiclass/tests/test_hierarchical_sampling.py

@@ -29,8 +29,8 @@ def test_hs_random_selecting(self):
         qseq = run_qs(ds, qs, self.y, len(self.y)-10)
         assert_array_equal(
             np.concatenate([qseq[:10], qseq[-10:]]),
-            np.array([48, 143, 13, 142, 88, 130, 29, 87, 36, 28,
-                      58, 137, 49, 105, 76, 71, 63, 47, 64, 55])
+            np.array([39, 126, 66, 135, 37, 33, 118, 132, 142, 144,
+                      71, 28, 63, 41, 140, 34, 20, 110, 136, 36])
             )
 
     def test_hs_active_selecting(self):
@@ -39,8 +39,8 @@ def test_hs_active_selecting(self):
         qseq = run_qs(ds, qs, self.y, len(self.y)-10)
         assert_array_equal(
             np.concatenate([qseq[:10], qseq[-10:]]),
-            np.array([48, 143, 13, 64, 101, 108, 51, 87, 36, 28,
-                      43, 118, 47, 25, 81, 82, 95, 40, 67, 120])
+            np.array([39, 126, 66, 135, 37, 33, 118, 132, 142, 144,
+                      89, 117, 48, 67, 75, 14, 79, 62, 105, 19])
             )
 
     def test_hs_subsampling(self):
@@ -52,7 +52,7 @@ def test_hs_subsampling(self):
         assert_array_equal(
             np.concatenate([qseq[:10], qseq[-10:]]),
             np.array([120, 50, 33, 28, 78, 133, 52, 124, 102, 109,
-                      81, 108, 12, 10, 89, 114, 92, 126, 48, 25])
+                      81, 108, 10, 89, 126, 114, 92, 48, 25, 13])
             )
 
     def test_hs_report_all_label(self):

libact/query_strategies/multilabel/tests/test_multilabel_realdata.py

@@ -47,7 +47,7 @@ def test_mmc(self):
         qs = MMC(trn_ds, random_state=1126)
         qseq = run_qs(trn_ds, qs, self.y, self.quota)
         assert_array_equal(qseq,
-                np.array([117, 655, 1350, 909, 1003, 1116, 546, 1055, 165, 1441]))
+                np.array([117, 655, 234, 1419, 1350, 1224, 427, 890, 1447, 103]))
 
     def test_multilabel_with_auxiliary_learner_hlr(self):
         trn_ds = Dataset(self.X,

requirements.txt

@@ -1,7 +1,7 @@
 setuptools
 numpy
 scipy
-scikit-learn<=0.19.2
+scikit-learn>=0.24
 matplotlib
 Cython
 joblib