Finish to fix sklearn dataset fetchers. Keep 20newsgroups_vectorized instead...

Finish to fix sklearn dataset fetchers. Keep 20newsgroups_vectorized instead of non vectorized version that is the preprocessed version of this text dataset. Remove kddcup99 dataset.

code/bolsonaro/data/dataset_loader.py

@@ -39,23 +39,20 @@ class DatasetLoader(object):
             dataset_loading_func = change_binary_func_load(load_breast_cancer)
             task = Task.BINARYCLASSIFICATION
         elif name == 'olivetti_faces':
-            data = fetch_olivetti_faces(random_state=dataset_parameters.random_state, shuffle=True)
-            task = Task.MULTICLASSIFICATION
-            X, y = data.data, data.target
-        elif name == '20newsgroups':
-            data = fetch_20newsgroups(random_state=dataset_parameters.random_state, shuffle=True)
-            #X, y = 
+            dataset = fetch_olivetti_faces(random_state=dataset_parameters.random_state, shuffle=True)
             task = Task.MULTICLASSIFICATION
+            X, y = dataset.data, dataset.target
         elif name == '20newsgroups_vectorized':
-            dataset_loading_func = fetch_20newsgroups_vectorized
+            dataset = fetch_20newsgroups_vectorized()
+            X, y = dataset.data, dataset.target
             task = Task.MULTICLASSIFICATION
         elif name == 'lfw_people':
-            data = fetch_lfw_people()
-            X, y = data.data, data.target
+            dataset = fetch_lfw_people()
+            X, y = dataset.data, dataset.target
             task = Task.MULTICLASSIFICATION
         elif name == 'lfw_pairs':
-            data = fetch_lfw_pairs()
-            X, y = data.data, data.target
+            dataset = fetch_lfw_pairs()
+            X, y = dataset.data, dataset.target
             task = Task.MULTICLASSIFICATION
         elif name == 'covtype':
             X, y = fetch_covtype(random_state=dataset_parameters.random_state, shuffle=True, return_X_y=True)
@@ -63,9 +60,6 @@ class DatasetLoader(object):
         elif name == 'rcv1':
             X, y = fetch_rcv1(random_state=dataset_parameters.random_state, shuffle=True, return_X_y=True)
             task = Task.MULTICLASSIFICATION
-        elif name == 'kddcup99':
-            X, y = fetch_kddcup99(random_state=dataset_parameters.random_state, shuffle=True, return_X_y=True)
-            task = Task.MULTICLASSIFICATION
         elif name == 'california_housing':
             X, y = fetch_california_housing(return_X_y=True)
             task = Task.REGRESSION