scikit-learn · qinhanmin2014 · Dec 18, 2019 · Dec 14, 2019 · Dec 14, 2019 · Dec 14, 2019
diff --git a/sklearn/_build_utils/deprecated_modules.py b/sklearn/_build_utils/deprecated_modules.py
@@ -47,9 +47,9 @@
      'SpectralBiclustering'),
     ('_birch', 'sklearn.cluster.birch', 'sklearn.cluster', 'Birch'),
     ('_dbscan', 'sklearn.cluster.dbscan_', 'sklearn.cluster', 'DBSCAN'),
-    ('_hierarchical', 'sklearn.cluster.hierarchical', 'sklearn.cluster',
+    ('_agglomerative', 'sklearn.cluster.hierarchical', 'sklearn.cluster',
      'FeatureAgglomeration'),
-    ('_k_means', 'sklearn.cluster.k_means_', 'sklearn.cluster', 'KMeans'),
+    ('_kmeans', 'sklearn.cluster.k_means_', 'sklearn.cluster', 'KMeans'),
     ('_mean_shift', 'sklearn.cluster.mean_shift_', 'sklearn.cluster',
      'MeanShift'),
     ('_optics', 'sklearn.cluster.optics_', 'sklearn.cluster', 'OPTICS'),
@@ -101,7 +101,7 @@
     ('_kernel_pca', 'sklearn.decomposition.kernel_pca',
      'sklearn.decomposition', 'KernelPCA'),
     ('_nmf', 'sklearn.decomposition.nmf', 'sklearn.decomposition', 'NMF'),
-    ('_online_lda', 'sklearn.decomposition.online_lda',
+    ('_lda', 'sklearn.decomposition.online_lda',
      'sklearn.decomposition', 'LatentDirichletAllocation'),
     ('_online_lda_fast', 'sklearn.decomposition.online_lda_fast',
      'sklearn.decomposition', 'mean_change'),
@@ -140,7 +140,7 @@
 
     ('_dict_vectorizer', 'sklearn.feature_extraction.dict_vectorizer',
      'sklearn.feature_extraction', 'DictVectorizer'),
-    ('_hashing', 'sklearn.feature_extraction.hashing',
+    ('_hash', 'sklearn.feature_extraction.hashing',
      'sklearn.feature_extraction', 'FeatureHasher'),
     ('_stop_words', 'sklearn.feature_extraction.stop_words',
      'sklearn.feature_extraction.text', 'ENGLISH_STOP_WORDS'),

diff --git a/sklearn/cluster/__init__.py b/sklearn/cluster/__init__.py
@@ -7,9 +7,9 @@
 from ._mean_shift import (mean_shift, MeanShift,
                           estimate_bandwidth, get_bin_seeds)
 from ._affinity_propagation import affinity_propagation, AffinityPropagation
-from ._hierarchical import (ward_tree, AgglomerativeClustering, linkage_tree,
-                            FeatureAgglomeration)
-from ._k_means import k_means, KMeans, MiniBatchKMeans
+from ._agglomerative import (ward_tree, AgglomerativeClustering,
+                             linkage_tree, FeatureAgglomeration)
+from ._kmeans import k_means, KMeans, MiniBatchKMeans
 from ._dbscan import dbscan, DBSCAN
 from ._optics import (OPTICS, cluster_optics_dbscan, compute_optics_graph,
                       cluster_optics_xi)

diff --git a/sklearn/cluster/_hierarchical.py → sklearn/cluster/_agglomerative.py b/sklearn/cluster/_hierarchical.py → sklearn/cluster/_agglomerative.py
@@ -25,7 +25,7 @@
 from ._feature_agglomeration import AgglomerationTransform
 from ..utils._fast_dict import IntFloatDict
 from ..utils.fixes import _astype_copy_false
-from ..utils import deprecated
+
 
 ###############################################################################
 # For non fully-connected graphs
@@ -249,8 +249,8 @@ def ward_tree(X, connectivity=None, n_clusters=None, return_distance=False):
     else:
         if n_clusters > n_samples:
             raise ValueError('Cannot provide more clusters than samples. '
-                             '%i n_clusters was asked, and there are %i samples.'
-                             % (n_clusters, n_samples))
+                             '%i n_clusters was asked, and there are %i '
+                             'samples.' % (n_clusters, n_samples))
         n_nodes = 2 * n_samples - n_clusters
 
     # create inertia matrix

diff --git a/sklearn/cluster/_k_means.py → sklearn/cluster/_kmeans.py b/sklearn/cluster/_k_means.py → sklearn/cluster/_kmeans.py
diff --git a/sklearn/cluster/_spectral.py b/sklearn/cluster/_spectral.py
@@ -15,7 +15,7 @@
 from ..metrics.pairwise import pairwise_kernels
 from ..neighbors import kneighbors_graph, NearestNeighbors
 from ..manifold import spectral_embedding
-from ._k_means import k_means
+from ._kmeans import k_means
 
 
 def discretize(vectors, copy=True, max_svd_restarts=30, n_iter_max=20,

diff --git a/sklearn/cluster/tests/test_hierarchical.py b/sklearn/cluster/tests/test_hierarchical.py
@@ -22,8 +22,9 @@
 
 from sklearn.cluster import ward_tree
 from sklearn.cluster import AgglomerativeClustering, FeatureAgglomeration
-from sklearn.cluster._hierarchical import (_hc_cut, _TREE_BUILDERS,
-                                           linkage_tree, _fix_connectivity)
+from sklearn.cluster._agglomerative import (_hc_cut, _TREE_BUILDERS,
+                                            linkage_tree,
+                                            _fix_connectivity)
 from sklearn.feature_extraction.image import grid_to_graph
 from sklearn.metrics.pairwise import PAIRED_DISTANCES, cosine_distances,\
     manhattan_distances, pairwise_distances

diff --git a/sklearn/cluster/tests/test_k_means.py b/sklearn/cluster/tests/test_k_means.py
@@ -22,8 +22,8 @@
 from sklearn.metrics.cluster import v_measure_score
 from sklearn.cluster import KMeans, k_means
 from sklearn.cluster import MiniBatchKMeans
-from sklearn.cluster._k_means import _labels_inertia
-from sklearn.cluster._k_means import _mini_batch_step
+from sklearn.cluster._kmeans import _labels_inertia
+from sklearn.cluster._kmeans import _mini_batch_step
 from sklearn.datasets import make_blobs
 from io import StringIO
 from sklearn.metrics.cluster import homogeneity_score
@@ -734,7 +734,7 @@ def test_k_means_function():
 
 def test_x_squared_norms_init_centroids():
     # Test that x_squared_norms can be None in _init_centroids
-    from sklearn.cluster._k_means import _init_centroids
+    from sklearn.cluster._kmeans import _init_centroids
 
     X_norms = np.sum(X**2, axis=1)
     precompute = _init_centroids(
@@ -921,7 +921,7 @@ def test_sample_weight_length():
 
 
 def test_check_normalize_sample_weight():
-    from sklearn.cluster._k_means import _check_normalize_sample_weight
+    from sklearn.cluster._kmeans import _check_normalize_sample_weight
     sample_weight = None
     checked_sample_weight = _check_normalize_sample_weight(sample_weight, X)
     assert _num_samples(X) == _num_samples(checked_sample_weight)

diff --git a/sklearn/decomposition/__init__.py b/sklearn/decomposition/__init__.py
@@ -16,7 +16,7 @@
                              MiniBatchDictionaryLearning, SparseCoder)
 from ._factor_analysis import FactorAnalysis
 from ..utils.extmath import randomized_svd
-from ._online_lda import LatentDirichletAllocation
+from ._lda import LatentDirichletAllocation
 
 __all__ = ['DictionaryLearning',
            'FastICA',

diff --git a/sklearn/decomposition/_online_lda.py → sklearn/decomposition/_lda.py b/sklearn/decomposition/_online_lda.py → sklearn/decomposition/_lda.py
diff --git a/sklearn/decomposition/tests/test_online_lda.py b/sklearn/decomposition/tests/test_online_lda.py
@@ -8,8 +8,8 @@
 import pytest
 
 from sklearn.decomposition import LatentDirichletAllocation
-from sklearn.decomposition._online_lda import (_dirichlet_expectation_1d,
-                                               _dirichlet_expectation_2d)
+from sklearn.decomposition._lda import (_dirichlet_expectation_1d,
+                                        _dirichlet_expectation_2d)
 
 from sklearn.utils._testing import assert_allclose
 from sklearn.utils._testing import assert_array_almost_equal

diff --git a/sklearn/feature_extraction/__init__.py b/sklearn/feature_extraction/__init__.py
@@ -5,7 +5,7 @@
 """
 
 from ._dict_vectorizer import DictVectorizer
-from ._hashing import FeatureHasher
+from ._hash import FeatureHasher
 from .image import img_to_graph, grid_to_graph
 from . import text
 

diff --git a/sklearn/feature_extraction/_hashing.py → sklearn/feature_extraction/_hash.py b/sklearn/feature_extraction/_hashing.py → sklearn/feature_extraction/_hash.py
diff --git a/sklearn/feature_extraction/text.py b/sklearn/feature_extraction/text.py
@@ -27,7 +27,7 @@
 
 from ..base import BaseEstimator, TransformerMixin
 from ..preprocessing import normalize
-from ._hashing import FeatureHasher
+from ._hash import FeatureHasher
 from ._stop_words import ENGLISH_STOP_WORDS
 from ..utils.validation import check_is_fitted, check_array, FLOAT_DTYPES
 from ..utils import _IS_32BIT, deprecated