[MRG] EHN add collections of imbalanced datasets

doc/api.rst

@@ -158,7 +158,7 @@ Functions
  :toctree: generated/
 
  datasets.make_imbalance
-
+ datasets.fetch_zenodo
 
 Utilities
 =========

doc/whats_new.rst

@@ -14,6 +14,8 @@ New features
 
 - Turn off steps in :class:`pipeline.Pipeline` using the `None`
  object. By `Christos Aridas`_.
+- Add a fetching method `datasets.fetch_zenodo` in order to get some
+ imbalanced datasets useful for benchmarking. By `Guillaume Lemaitre`_.
 
 Enhancement
 ~~~~~~~~~~~

imblearn/datasets/__init__.py

@@ -4,5 +4,7 @@
 """
 
 from .imbalance import make_imbalance
+from .zenodo import fetch_zenodo
 
-__all__ = ['make_imbalance']
+__all__ = ['make_imbalance',
+ 'fetch_zenodo']

imblearn/datasets/tests/test_zenodo.py

@@ -0,0 +1,92 @@
+"""Test the zenodo loader.
+
+Skipped if zenodo is not already downloaded to data_home.
+"""
+from imblearn.datasets import fetch_zenodo
+from sklearn.utils.testing import (assert_equal, assert_allclose,
+ assert_raises_regex, SkipTest)
+
+DATASET_SHAPE = {'ecoli': (336, 7),
+ 'optical_digits': (5620, 64),
+ 'satimage': (6435, 36),
+ 'pen_digits': (10992, 16),
+ 'abalone': (4177, 10),
+ 'sick_euthyroid': (3163, 42),
+ 'spectrometer': (531, 93),
+ 'car_eval_34': (1728, 21),
+ 'isolet': (7797, 617),
+ 'us_crime': (1994, 100),
+ 'yeast_ml8': (2417, 103),
+ 'scene': (2407, 294),
+ 'libras_move': (360, 90),
+ 'thyroid_sick': (3772, 52),
+ 'coil_2000': (9822, 85),
+ 'arrhythmia': (452, 278),
+ 'solar_flare_m0': (1389, 32),
+ 'oil': (937, 49),
+ 'car_eval_4': (1728, 21),
+ 'wine_quality': (4898, 11),
+ 'letter_img': (20000, 16),
+ 'yeast_me2': (1484, 8),
+ 'webpage': (34780, 300),
+ 'ozone_level': (2536, 72),
+ 'mammography': (11183, 6),
+ 'protein_homo': (145751, 74),
+ 'abalone_19': (4177, 10)}
+
+
+def fetch(*args, **kwargs):
+ return fetch_zenodo(*args, download_if_missing=True, **kwargs)
+
+
+def test_fetch():
+ try:
+ datasets1 = fetch(shuffle=True, random_state=42)
+ except IOError:
+ raise SkipTest("Zenodo dataset can not be loaded.")
+
+ datasets2 = fetch(shuffle=True, random_state=37)
+
+ for k in DATASET_SHAPE.keys():
+
+ X1, X2 = datasets1[k].data, datasets2[k].data
+ assert_equal(DATASET_SHAPE[k], X1.shape)
+ assert_equal(X1.shape, X2.shape)
+
+ assert_allclose(X1.sum(), X2.sum())
+
+ y1, y2 = datasets1[k].target, datasets2[k].target
+ assert_equal((X1.shape[0],), y1.shape)
+ assert_equal((X1.shape[0],), y2.shape)
+
+
+def test_fetch_filter():
+ try:
+ datasets1 = fetch(filter_data=tuple([1]), shuffle=True,
+ random_state=42)
+ except IOError:
+ raise SkipTest("Zenodo dataset can not be loaded.")
+
+ datasets2 = fetch(filter_data=tuple(['ecoli']), shuffle=True,
+ random_state=37)
+
+ X1, X2 = datasets1['ecoli'].data, datasets2['ecoli'].data
+ assert_equal(DATASET_SHAPE['ecoli'], X1.shape)
+ assert_equal(X1.shape, X2.shape)
+
+ assert_allclose(X1.sum(), X2.sum())
+
+ y1, y2 = datasets1['ecoli'].target, datasets2['ecoli'].target
+ assert_equal((X1.shape[0],), y1.shape)
+ assert_equal((X1.shape[0],), y2.shape)
+
+
+def test_fetch_error():
+ assert_raises_regex(ValueError, 'is not a dataset available.',
+ fetch_zenodo, filter_data=tuple(['rnd']))
+ assert_raises_regex(ValueError, 'dataset with the ID=',
+ fetch_zenodo, filter_data=tuple([-1]))
+ assert_raises_regex(ValueError, 'dataset with the ID=',
+ fetch_zenodo, filter_data=tuple([100]))
+ assert_raises_regex(ValueError, 'value in the tuple',
+ fetch_zenodo, filter_data=tuple([1.00]))