From d3601a40483fac5ea68680052dce998aa3a0db7c Mon Sep 17 00:00:00 2001
From: Dominique Benielli <dominique.benielli@lis-lab.fr>
Date: Thu, 23 Jul 2020 16:07:11 +0200
Subject: [PATCH] change cumbo to combo
---
copyrightstamp.txt | 2 +-
doc/reference/api.rst | 2 +-
...x_glr_plot_cumbo_2_views_2_classes_001.png | Bin
...x_glr_plot_cumbo_3_views_3_classes_001.png | Bin
...glr_plot_cumbo_2_views_2_classes_thumb.png | Bin
...glr_plot_cumbo_3_views_3_classes_thumb.png | Bin
.../plot_cumbo_2_views_2_classes.ipynb | 0
.../plot_cumbo_2_views_2_classes.py | 0
.../plot_cumbo_2_views_2_classes.py.md5 | 0
.../plot_cumbo_2_views_2_classes.rst | 0
...lot_cumbo_2_views_2_classes_codeobj.pickle | Bin
.../plot_cumbo_3_views_3_classes.ipynb | 0
.../plot_cumbo_3_views_3_classes.py | 0
.../plot_cumbo_3_views_3_classes.py.md5 | 0
.../plot_cumbo_3_views_3_classes.rst | 0
...lot_cumbo_3_views_3_classes_codeobj.pickle | Bin
.../{cumbo => combo}/sg_execution_times.rst | 0
examples/{cumbo => combo}/README.txt | 0
.../plot_combo_2_views_2_classes.py} | 4 +-
.../plot_combo_3_views_3_classes.py} | 8 +-
...CuBo.py => plot_usecase_exampleMuComBo.py} | 2 +-
multimodal/boosting/__init__.py | 4 +-
multimodal/boosting/boost.py | 4 +-
multimodal/boosting/{cumbo.py => combo.py} | 26 ++--
multimodal/boosting/mumbo.py | 2 +-
multimodal/kernels/lpMKL.py | 2 +-
multimodal/kernels/mkernel.py | 2 +-
multimodal/kernels/mvml.py | 2 +-
.../tests/{test_cumbo.py => test_combo.py} | 140 +++++++++---------
multimodal/tests/test_data_sample.py | 2 +-
multimodal/tests/test_mkl.py | 2 +-
multimodal/tests/test_mumbo.py | 2 +-
multimodal/tests/test_mvml.py | 2 +-
setup.py | 2 +-
34 files changed, 105 insertions(+), 105 deletions(-)
rename doc/tutorial/auto_examples/{cumbo => combo}/images/sphx_glr_plot_cumbo_2_views_2_classes_001.png (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/images/sphx_glr_plot_cumbo_3_views_3_classes_001.png (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/images/thumb/sphx_glr_plot_cumbo_2_views_2_classes_thumb.png (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/images/thumb/sphx_glr_plot_cumbo_3_views_3_classes_thumb.png (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_2_views_2_classes.ipynb (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_2_views_2_classes.py (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_2_views_2_classes.py.md5 (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_2_views_2_classes.rst (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_2_views_2_classes_codeobj.pickle (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_3_views_3_classes.ipynb (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_3_views_3_classes.py (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_3_views_3_classes.py.md5 (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_3_views_3_classes.rst (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/plot_cumbo_3_views_3_classes_codeobj.pickle (100%)
rename doc/tutorial/auto_examples/{cumbo => combo}/sg_execution_times.rst (100%)
rename examples/{cumbo => combo}/README.txt (100%)
rename examples/{cumbo/plot_cumbo_2_views_2_classes.py => combo/plot_combo_2_views_2_classes.py} (97%)
rename examples/{cumbo/plot_cumbo_3_views_3_classes.py => combo/plot_combo_3_views_3_classes.py} (95%)
rename examples/usecase/{plot_usecase_exampleMuCuBo.py => plot_usecase_exampleMuComBo.py} (98%)
rename multimodal/boosting/{cumbo.py => combo.py} (97%)
rename multimodal/tests/{test_cumbo.py => test_combo.py} (93%)
diff --git a/copyrightstamp.txt b/copyrightstamp.txt
index b3d76ec..c863e02 100644
--- a/copyrightstamp.txt
+++ b/copyrightstamp.txt
@@ -23,7 +23,7 @@ Description:
-----------
The multimodal package implement classifiers multiview,
-MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
compatible with sklearn
Version:
diff --git a/doc/reference/api.rst b/doc/reference/api.rst
index e680643..da894f4 100644
--- a/doc/reference/api.rst
+++ b/doc/reference/api.rst
@@ -23,7 +23,7 @@ multimodal.boosting.mumbo
multimodal.boosting.cumbo
+++++++++++++++++++++++++
-.. automodule:: multimodal.boosting.cumbo
+.. automodule:: multimodal.boosting.combo
:members:
:inherited-members:
diff --git a/doc/tutorial/auto_examples/cumbo/images/sphx_glr_plot_cumbo_2_views_2_classes_001.png b/doc/tutorial/auto_examples/combo/images/sphx_glr_plot_cumbo_2_views_2_classes_001.png
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/images/sphx_glr_plot_cumbo_2_views_2_classes_001.png
rename to doc/tutorial/auto_examples/combo/images/sphx_glr_plot_cumbo_2_views_2_classes_001.png
diff --git a/doc/tutorial/auto_examples/cumbo/images/sphx_glr_plot_cumbo_3_views_3_classes_001.png b/doc/tutorial/auto_examples/combo/images/sphx_glr_plot_cumbo_3_views_3_classes_001.png
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/images/sphx_glr_plot_cumbo_3_views_3_classes_001.png
rename to doc/tutorial/auto_examples/combo/images/sphx_glr_plot_cumbo_3_views_3_classes_001.png
diff --git a/doc/tutorial/auto_examples/cumbo/images/thumb/sphx_glr_plot_cumbo_2_views_2_classes_thumb.png b/doc/tutorial/auto_examples/combo/images/thumb/sphx_glr_plot_cumbo_2_views_2_classes_thumb.png
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/images/thumb/sphx_glr_plot_cumbo_2_views_2_classes_thumb.png
rename to doc/tutorial/auto_examples/combo/images/thumb/sphx_glr_plot_cumbo_2_views_2_classes_thumb.png
diff --git a/doc/tutorial/auto_examples/cumbo/images/thumb/sphx_glr_plot_cumbo_3_views_3_classes_thumb.png b/doc/tutorial/auto_examples/combo/images/thumb/sphx_glr_plot_cumbo_3_views_3_classes_thumb.png
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/images/thumb/sphx_glr_plot_cumbo_3_views_3_classes_thumb.png
rename to doc/tutorial/auto_examples/combo/images/thumb/sphx_glr_plot_cumbo_3_views_3_classes_thumb.png
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes.ipynb b/doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes.ipynb
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes.ipynb
rename to doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes.ipynb
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes.py b/doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes.py
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes.py
rename to doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes.py
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes.py.md5 b/doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes.py.md5
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes.py.md5
rename to doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes.py.md5
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes.rst b/doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes.rst
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes.rst
rename to doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes.rst
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes_codeobj.pickle b/doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes_codeobj.pickle
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_2_views_2_classes_codeobj.pickle
rename to doc/tutorial/auto_examples/combo/plot_cumbo_2_views_2_classes_codeobj.pickle
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes.ipynb b/doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes.ipynb
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes.ipynb
rename to doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes.ipynb
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes.py b/doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes.py
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes.py
rename to doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes.py
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes.py.md5 b/doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes.py.md5
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes.py.md5
rename to doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes.py.md5
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes.rst b/doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes.rst
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes.rst
rename to doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes.rst
diff --git a/doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes_codeobj.pickle b/doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes_codeobj.pickle
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/plot_cumbo_3_views_3_classes_codeobj.pickle
rename to doc/tutorial/auto_examples/combo/plot_cumbo_3_views_3_classes_codeobj.pickle
diff --git a/doc/tutorial/auto_examples/cumbo/sg_execution_times.rst b/doc/tutorial/auto_examples/combo/sg_execution_times.rst
similarity index 100%
rename from doc/tutorial/auto_examples/cumbo/sg_execution_times.rst
rename to doc/tutorial/auto_examples/combo/sg_execution_times.rst
diff --git a/examples/cumbo/README.txt b/examples/combo/README.txt
similarity index 100%
rename from examples/cumbo/README.txt
rename to examples/combo/README.txt
diff --git a/examples/cumbo/plot_cumbo_2_views_2_classes.py b/examples/combo/plot_combo_2_views_2_classes.py
similarity index 97%
rename from examples/cumbo/plot_cumbo_2_views_2_classes.py
rename to examples/combo/plot_combo_2_views_2_classes.py
index 77d0588..7c25791 100644
--- a/examples/cumbo/plot_cumbo_2_views_2_classes.py
+++ b/examples/combo/plot_combo_2_views_2_classes.py
@@ -23,7 +23,7 @@ rightly classify the points.
"""
import numpy as np
-from multimodal.boosting.cumbo import MuCumboClassifier
+from multimodal.boosting.combo import MuComboClassifier
from matplotlib import pyplot as plt
@@ -59,7 +59,7 @@ y[2*n_samples:] = 1
views_ind = np.array([0, 2, 4])
n_estimators = 3
-clf = MuCumboClassifier(n_estimators=n_estimators)
+clf = MuComboClassifier(n_estimators=n_estimators)
clf.fit(X, y, views_ind)
print('\nAfter 3 iterations, the MuCuMBo classifier reaches exact '
diff --git a/examples/cumbo/plot_cumbo_3_views_3_classes.py b/examples/combo/plot_combo_3_views_3_classes.py
similarity index 95%
rename from examples/cumbo/plot_cumbo_3_views_3_classes.py
rename to examples/combo/plot_combo_3_views_3_classes.py
index 058b2dc..205c61d 100644
--- a/examples/cumbo/plot_cumbo_3_views_3_classes.py
+++ b/examples/combo/plot_combo_3_views_3_classes.py
@@ -1,7 +1,7 @@
# -*- coding: utf-8 -*-
"""
==================================
-MuCumbo 3 views, 3 classes example
+MuCombo 3 views, 3 classes example
==================================
In this toy example, we generate data from three classes, split between three
@@ -12,12 +12,12 @@ well seperated, while the points for the third class are not seperated with
the two other classes. That means that, taken separately, none of the single
views allows for a good classification of the data.
-Nevertheless, the MuCuMbo algorithm take adavantage of the complementarity of
+Nevertheless, the MuCoMbo algorithm take adavantage of the complementarity of
the views to rightly classify the points.
"""
import numpy as np
-from multimodal.boosting.cumbo import MuCumboClassifier
+from multimodal.boosting.combo import MuComboClassifier
from matplotlib import pyplot as plt
@@ -56,7 +56,7 @@ y[2*n_samples:] = 2
views_ind = np.array([0, 2, 4, 6])
n_estimators = 4
-clf = MuCumboClassifier(n_estimators=n_estimators)
+clf = MuComboClassifier(n_estimators=n_estimators)
clf.fit(X, y, views_ind)
print('\nAfter 4 iterations, the MuCuMBo classifier reaches exact '
diff --git a/examples/usecase/plot_usecase_exampleMuCuBo.py b/examples/usecase/plot_usecase_exampleMuComBo.py
similarity index 98%
rename from examples/usecase/plot_usecase_exampleMuCuBo.py
rename to examples/usecase/plot_usecase_exampleMuComBo.py
index f3d7254..dc6ddba 100644
--- a/examples/usecase/plot_usecase_exampleMuCuBo.py
+++ b/examples/usecase/plot_usecase_exampleMuComBo.py
@@ -20,7 +20,7 @@ from multimodal.datasets.base import load_dict, save_dict
from multimodal.tests.data.get_dataset_path import get_dataset_path
from multimodal.datasets.data_sample import MultiModalArray
-from multimodal.boosting.cumbo import MuCumboClassifier
+from multimodal.boosting.combo import MuComboClassifier
import numpy as np
import matplotlib.pyplot as plt
import matplotlib._color_data as mcd
diff --git a/multimodal/boosting/__init__.py b/multimodal/boosting/__init__.py
index bb0d1af..7aaa2a2 100644
--- a/multimodal/boosting/__init__.py
+++ b/multimodal/boosting/__init__.py
@@ -1,6 +1,6 @@
from .mumbo import MumboClassifier
-from .cumbo import MuCumboClassifier
+from .combo import MuComboClassifier
-__all__ = ['MumboClassifier', 'MuCumboClassifier']
+__all__ = ['MumboClassifier', 'MuComboClassifier']
diff --git a/multimodal/boosting/boost.py b/multimodal/boosting/boost.py
index 3fd7f15..182a1fd 100644
--- a/multimodal/boosting/boost.py
+++ b/multimodal/boosting/boost.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
@@ -53,7 +53,7 @@ from multimodal.datasets.data_sample import MultiModalData, MultiModalArray, Mul
class UBoosting(metaclass=ABCMeta):
"""
- Abstract class MuCumboClassifier and MumboClassifier should inherit from
+ Abstract class MuComboClassifier and MumboClassifier should inherit from
UBoosting for methods
"""
diff --git a/multimodal/boosting/cumbo.py b/multimodal/boosting/combo.py
similarity index 97%
rename from multimodal/boosting/cumbo.py
rename to multimodal/boosting/combo.py
index d32965b..2adfa87 100644
--- a/multimodal/boosting/cumbo.py
+++ b/multimodal/boosting/combo.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
@@ -42,7 +42,7 @@
r"""
This module contains a **Mu**\ lti\ **C**\ onfusion **M**\ Matrix **B**\ osting (**CuMBo**)
-estimator for classification implemented in the ``MuCumboClassifier`` class.
+estimator for classification implemented in the ``MuComboClassifier`` class.
"""
import numpy as np
@@ -61,7 +61,7 @@ from .boost import UBoosting
import warnings
-class MuCumboClassifier(BaseEnsemble, ClassifierMixin, UBoosting):
+class MuComboClassifier(BaseEnsemble, ClassifierMixin, UBoosting):
r"""It then iterates the process on the same dataset but where the weights of
incorrectly classified instances are adjusted such that subsequent
classifiers focus more on difficult cases.
@@ -121,27 +121,27 @@ class MuCumboClassifier(BaseEnsemble, ClassifierMixin, UBoosting):
Examples
--------
- >>> from multimodal.boosting.cumbo import MuCumboClassifier
+ >>> from multimodal.boosting.cumbo import MuComboClassifier
>>> from sklearn.datasets import load_iris
>>> X, y = load_iris(return_X_y=True)
>>> views_ind = [0, 2, 4] # view 0: sepal data, view 1: petal data
- >>> clf = MuCumboClassifier(random_state=0)
+ >>> clf = MuComboClassifier(random_state=0)
>>> clf.fit(X, y, views_ind) # doctest: +NORMALIZE_WHITESPACE
- MuCumboClassifier(base_estimator=None, n_estimators=50, random_state=0)
+ MuComboClassifier(base_estimator=None, n_estimators=50, random_state=0)
>>> print(clf.predict([[ 5., 3., 1., 1.]]))
[0]
>>> views_ind = [[0, 2], [1, 3]] # view 0: length data, view 1: width data
- >>> clf = MuCumboClassifier(random_state=0)
+ >>> clf = MuComboClassifier(random_state=0)
>>> clf.fit(X, y, views_ind) # doctest: +NORMALIZE_WHITESPACE
- MuCumboClassifier(base_estimator=None, n_estimators=50, random_state=0)
+ MuComboClassifier(base_estimator=None, n_estimators=50, random_state=0)
>>> print(clf.predict([[ 5., 3., 1., 1.]]))
[0]
>>> from sklearn.tree import DecisionTreeClassifier
>>> base_estimator = DecisionTreeClassifier(max_depth=2)
- >>> clf = MuCumboClassifier(base_estimator=base_estimator, random_state=1)
+ >>> clf = MuComboClassifier(base_estimator=base_estimator, random_state=1)
>>> clf.fit(X, y, views_ind) # doctest: +NORMALIZE_WHITESPACE
- MuCumboClassifier(base_estimator=DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=2,
+ MuComboClassifier(base_estimator=DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=2,
max_features=None, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=2,
@@ -177,14 +177,14 @@ class MuCumboClassifier(BaseEnsemble, ClassifierMixin, UBoosting):
base_estimator=None,
n_estimators=50,
random_state=None): # n_estimators=50,
- super(MuCumboClassifier, self).__init__(
+ super(MuComboClassifier, self).__init__(
base_estimator=base_estimator,
n_estimators=n_estimators)
self.random_state = random_state
def _validate_estimator(self):
"""Check the estimator and set the base_estimator_ attribute."""
- super(MuCumboClassifier, self)._validate_estimator(
+ super(MuComboClassifier, self)._validate_estimator(
default=DecisionTreeClassifier(max_depth=1))
if not has_fit_parameter(self.base_estimator_, "sample_weight"):
@@ -688,7 +688,7 @@ class MuCumboClassifier(BaseEnsemble, ClassifierMixin, UBoosting):
score : float
Mean accuracy of self.predict(X) wrt. y.
"""
- return super(MuCumboClassifier, self).score(X, y)
+ return super(MuComboClassifier, self).score(X, y)
def staged_score(self, X, y):
"""Return staged mean accuracy on the given test data and labels.
diff --git a/multimodal/boosting/mumbo.py b/multimodal/boosting/mumbo.py
index 90d4704..4b5244b 100644
--- a/multimodal/boosting/mumbo.py
+++ b/multimodal/boosting/mumbo.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
diff --git a/multimodal/kernels/lpMKL.py b/multimodal/kernels/lpMKL.py
index f0c33d9..12f6901 100644
--- a/multimodal/kernels/lpMKL.py
+++ b/multimodal/kernels/lpMKL.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
diff --git a/multimodal/kernels/mkernel.py b/multimodal/kernels/mkernel.py
index a6b7527..7334e79 100644
--- a/multimodal/kernels/mkernel.py
+++ b/multimodal/kernels/mkernel.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
diff --git a/multimodal/kernels/mvml.py b/multimodal/kernels/mvml.py
index 9a3a4c6..e261661 100644
--- a/multimodal/kernels/mvml.py
+++ b/multimodal/kernels/mvml.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
diff --git a/multimodal/tests/test_cumbo.py b/multimodal/tests/test_combo.py
similarity index 93%
rename from multimodal/tests/test_cumbo.py
rename to multimodal/tests/test_combo.py
index 0c5176e..52c59f0 100644
--- a/multimodal/tests/test_cumbo.py
+++ b/multimodal/tests/test_combo.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
@@ -60,11 +60,11 @@ from sklearn.linear_model import Lasso
from sklearn.tree import DecisionTreeClassifier
from sklearn import datasets
from sklearn.utils.estimator_checks import check_estimator
-from multimodal.boosting.cumbo import MuCumboClassifier
+from multimodal.boosting.combo import MuComboClassifier
from multimodal.tests.data.get_dataset_path import get_dataset_path
from multimodal.datasets.data_sample import MultiModalArray
-class TestMuCumboClassifier(unittest.TestCase):
+class TestMuComboClassifier(unittest.TestCase):
@classmethod
def setUpClass(clf):
@@ -75,11 +75,11 @@ class TestMuCumboClassifier(unittest.TestCase):
def test_init(self):
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
self.assertEqual(clf.random_state, None)
self.assertEqual(clf.n_estimators, 50)
n_estimators = 3
- clf = MuCumboClassifier(n_estimators=n_estimators)
+ clf = MuComboClassifier(n_estimators=n_estimators)
#self.assertEqual(clf.view_mode_)
def test_init_var(self):
@@ -98,7 +98,7 @@ class TestMuCumboClassifier(unittest.TestCase):
expected_predicted_classes_shape = ((n_views, y.shape[0]))
expected_n_yi_s = np.array([1, 1, 2])
expected_beta_class = np.ones((n_views, n_classes)) / n_classes
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.n_classes_ = n_classes
(cost, label_score, label_score_glob, predicted_classes, score_function, beta_class, n_yi_s) \
= clf._init_var(n_views, y)
@@ -121,7 +121,7 @@ class TestMuCumboClassifier(unittest.TestCase):
expected_dist = np.array(
[[0.25, 0.25, 0.25, 0.25], [0.5, 0.5, -2., 2.], [-0.5, 0.5, -1., 2.]])
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
dist = clf._compute_dist(cost, y)
np.testing.assert_equal(dist, expected_dist)
@@ -156,7 +156,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# expected_coop_coef = np.array([[1, 0, 1, 0], [1, 1, 1, 0], [0, 0, 1, 1]],
# dtype=np.float64)
#
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# coop_coef = clf._compute_coop_coef(predicted_classes, y)
#
# assert_array_equal(coop_coef, expected_coop_coef)
@@ -172,7 +172,7 @@ class TestMuCumboClassifier(unittest.TestCase):
y = np.array([0, 2, 1, 2])
expected_edges = np.array([1.25, 0.75, 0.25])
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
edges = clf._compute_edges(cost, predicted_classes, y)
np.testing.assert_equal(edges, expected_edges)
@@ -183,7 +183,7 @@ class TestMuCumboClassifier(unittest.TestCase):
expected_alpha = 0.5
edge = (np.e-1.) / (np.e+1.)
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
alpha = clf._compute_alphas(edge)
self.assertAlmostEqual(alpha, expected_alpha, decimal)
@@ -197,7 +197,7 @@ class TestMuCumboClassifier(unittest.TestCase):
def test_prepare_beta_solver(self):
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.n_views_ = 3
clf.n_classes_ = 3
A, b, G, h, l = clf._prepare_beta_solver()
@@ -239,7 +239,7 @@ class TestMuCumboClassifier(unittest.TestCase):
self.assertEqual(l, {'l': 18})
def test_solver_cp_forbeta(self):
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.n_views_ = 3
clf.n_classes_ = 3
clf.n_yi_ = np.array([1, 1, 2])
@@ -265,7 +265,7 @@ class TestMuCumboClassifier(unittest.TestCase):
np.testing.assert_almost_equal(s_r, np.ones(3, dtype=np.float), 9)
def test_solver_compute_betas(self):
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.n_views_ = 3
clf.n_classes_ = 3
clf.n_yi_ = np.array([1, 1, 2])
@@ -295,7 +295,7 @@ class TestMuCumboClassifier(unittest.TestCase):
def test_indicatrice(self):
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.n_views_ = 3
clf.n_classes_ = 3
y_i = np.array([0, 1, 2, 0])
@@ -331,7 +331,7 @@ class TestMuCumboClassifier(unittest.TestCase):
[[-2, 1, 0.5], [1, 1, -1], [1, -2, 0.5], [1, 1, -1]]],
dtype=np.float64)
score_function_Tminus1 =10 *np.ones((3,4,3), dtype=np.float)
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.n_views_ = 3
clf.n_classes_ = 3
clf.n_yi_ = np.array([1, 1, 2])
@@ -380,7 +380,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# [[8, 2, -4], [2, 4, 0.], [4, 1, -2], [8, 4., 1]]],
# dtype=np.float64)
#
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# cost, label_score = clf._compute_cost(label_score, pred_classes, y, alphas,
# use_coop_coef=True)
#
@@ -413,7 +413,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# [[-9., 1., 8.], [1., 0.125, -1.125], [4., -4.5, 0.5], [1., 8., -9.]]],
# dtype=np.float64)
#
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# cost, label_score = clf._compute_cost(label_score, pred_classes, y, alphas,
# use_coop_coef=False)
#
@@ -447,7 +447,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# [[-2., 1., 1.], [1., 0.125, -1.125], [0.5, -1., 0.5], [1., 8., -9.]]],
# dtype=np.float64)
#
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# cost, label_score = clf._compute_cost(label_score, pred_classes, y, alphas,
# use_coop_coef=True)
#
@@ -461,19 +461,19 @@ class TestMuCumboClassifier(unittest.TestCase):
#
# n_estimators = 10
#
- # clf = MuCumboClassifier(n_estimators=n_estimators, best_view_mode='edge')
+ # clf = MuComboClassifier(n_estimators=n_estimators, best_view_mode='edge')
# clf.fit(iris.data, iris.target, iris.views_ind)
# score = clf.score(iris.data, iris.target)
# assert_greater(score, 0.95, "Failed with score = {}".format(score))
#
- # clf = MuCumboClassifier(n_estimators=n_estimators, best_view_mode='error')
+ # clf = MuComboClassifier(n_estimators=n_estimators, best_view_mode='error')
# clf.fit(iris.data, iris.target, iris.views_ind)
# score = clf.score(iris.data, iris.target)
# assert_greater(score, 0.95, "Failed with score = {}".format(score))
#
- # assert_raises(ValueError, MuCumboClassifier(), best_view_mode='test')
+ # assert_raises(ValueError, MuComboClassifier(), best_view_mode='test')
#
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.best_view_mode = 'test'
# assert_raises(ValueError, clf.fit, iris.data, iris.target, iris.views_ind)
#
@@ -483,7 +483,7 @@ class TestMuCumboClassifier(unittest.TestCase):
X = np.array([[1., 1., 1.], [-1., -1., -1.]])
y = np.array([0, 1])
expected_views_ind = np.array([0, 1, 3])
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.fit(X, y)
# np.testing.assert_equal(clf.X_.views_ind, expected_views_ind)
@@ -495,12 +495,12 @@ class TestMuCumboClassifier(unittest.TestCase):
X = np.array([[1., 1., 1.], [-1., -1., -1.]])
views_ind = np.array([0, 1, 3])
y = np.array([3, 1])
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.fit(X, y, views_ind)
np.testing.assert_almost_equal(clf.predict(X), y)
y = np.array(["class_1", "class_2"])
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.fit(X, y)
np.testing.assert_equal(clf.predict(X), y)
# Check that misformed or inconsistent inputs raise expections
@@ -517,70 +517,70 @@ class TestMuCumboClassifier(unittest.TestCase):
# X = np.array([[1., 1., 1.], [-1., -1., -1.]])
# y = np.array([1])
# views_ind = np.array([0, 1, 3])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# y = np.array([1, 0, 0, 1])
# views_ind = np.array([0, 1, 3])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# y = np.array([3.2, 1.1])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# y = np.array([0, 1])
# views_ind = np.array([0, 3, 1])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array([-1, 1, 3])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array([0, 1, 4])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array([0.5, 1, 3])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array("test")
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.zeros((3, 2, 4))
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array([[-1], [1, 2]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array([[3], [1, 2]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array([[0.5], [1, 2]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array([[-1, 0], [1, 2]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array([[0, 3], [1, 2]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
# views_ind = np.array([[0.5], [1], [2]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y, views_ind)
#
#
def test_decision_function(self):
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.fit(self.iris.data, self.iris.target, self.iris.views_ind)
X = np.zeros((4, 3))
with self.assertRaises(ValueError):
@@ -591,7 +591,7 @@ class TestMuCumboClassifier(unittest.TestCase):
np.testing.assert_almost_equal(dec, dec_expected, 9)
def test_predict(self):
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
X = np.array([[0., 0.5, 0.7], [1., 1.5, 1.7], [2., 2.5, 2.7]])
y = np.array([1, 1, 1])
clf.fit(X, y)
@@ -605,13 +605,13 @@ class TestMuCumboClassifier(unittest.TestCase):
# # Check that using empty data raises an exception
# X = np.array([[]])
# y = np.array([])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# assert_raises(ValueError, clf.fit, X, y)
#
# # Check that fit() works for the smallest possible dataset
# X = np.array([[0.]])
# y = np.array([0])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(X, y)
# assert_array_equal(clf.predict(X), y)
# assert_array_equal(clf.predict(np.array([[1.]])), np.array([0]))
@@ -620,7 +620,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# X = np.array([[0., 0.5, 0.7], [1., 1.5, 1.7], [2., 2.5, 2.7]])
# y = np.array([1, 1, 1])
# views_ind = np.array([0, 1, 3])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(X, y, views_ind)
# assert_array_equal(clf.predict(X), y)
# assert_array_equal(clf.predict(np.array([[-1., 0., 1.]])), np.array([1]))
@@ -628,7 +628,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# X = np.array([[0., 0.5, 0.7], [1., 1.5, 1.7], [2., 2.5, 2.7]])
# y = np.array([1, 1, 1])
# views_ind = np.array([[0, 2], [1]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(X, y, views_ind)
# assert_array_equal(clf.predict(X), y)
# assert_array_equal(clf.predict(np.array([[-1., 0., 1.]])), np.array([1]))
@@ -647,7 +647,7 @@ class TestMuCumboClassifier(unittest.TestCase):
[-0.3, -1.3]])
y = np.array([0, 0, 0, 1, 1, 1])
views_ind = np.array([0, 2])
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.fit(X, y, views_ind)
#assert_array_equal(clf.predict(X), y)
#assert_array_equal(clf.predict(np.array([[1., 1.], [-1., -1.]])),
@@ -655,7 +655,7 @@ class TestMuCumboClassifier(unittest.TestCase):
#assert_equal(clf.decision_function(X).shape, y.shape)
views_ind = np.array([[1, 0]])
- clf = MuCumboClassifier()
+ clf = MuComboClassifier()
clf.fit(X, y, views_ind)
np.testing.assert_almost_equal(clf.predict(X), y)
@@ -676,7 +676,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# [-0.3, -1.3, -1.4]])
# y = np.array([0, 0, 0, 1, 1, 1])
# views_ind = np.array([0, 2, 3])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(X, y, views_ind)
# assert_array_equal(clf.predict(X), y)
# assert_array_equal(clf.predict(np.array([[1., 1., 1.], [-1., -1., -1.]])),
@@ -684,7 +684,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# assert_equal(clf.decision_function(X).shape, y.shape)
#
# views_ind = np.array([[2, 0], [1]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(X, y, views_ind)
# assert_array_equal(clf.predict(X), y)
# assert_array_equal(clf.predict(np.array([[1., 1., 1.], [-1., -1., -1.]])),
@@ -701,7 +701,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# [-0.3, -1.3, -1.4, -0.6, -0.7]])
# y = np.array([0, 0, 0, 1, 1, 1])
# views_ind = np.array([0, 2, 3, 5])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(X, y, views_ind)
# assert_array_equal(clf.predict(X), y)
# data = np.array([[1., 1., 1., 1., 1.], [-1., -1., -1., -1., -1.]])
@@ -709,7 +709,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# assert_equal(clf.decision_function(X).shape, y.shape)
#
# views_ind = np.array([[2, 0], [1], [3, 4]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(X, y, views_ind)
# assert_array_equal(clf.predict(X), y)
# data = np.array([[1., 1., 1., 1., 1.], [-1., -1., -1., -1., -1.]])
@@ -726,7 +726,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# [-0.3, -1.3, -1.4, -0.6, -0.7]])
# y = np.array([0, 0, 1, 1, 2, 2])
# views_ind = np.array([0, 2, 3, 5])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(X, y, views_ind)
# assert_array_equal(clf.predict(X), y)
# data = np.array(
@@ -737,7 +737,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# assert_equal(clf.decision_function(X).shape, (X.shape[0], 3))
#
# views_ind = np.array([[1, 0], [2], [3, 4]])
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(X, y, views_ind)
# assert_array_equal(clf.predict(X), y)
# data = np.array(
@@ -767,7 +767,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# y = np.zeros(2*n_samples, dtype=np.int64)
# y[n_samples:] = 1
# views_ind = np.array([0, 2, 4])
- # clf = MuCumboClassifier(n_estimators=1)
+ # clf = MuComboClassifier(n_estimators=1)
# clf.fit(X, y, views_ind)
# assert_equal(clf.score(X, y), 1.)
#
@@ -786,7 +786,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# y = np.zeros(4*n_samples, dtype=np.int64)
# y[2*n_samples:] = 1
# views_ind = np.array([0, 2, 4])
- # clf = MuCumboClassifier(n_estimators=3)
+ # clf = MuComboClassifier(n_estimators=3)
# clf.fit(X, y, views_ind)
# assert_equal(clf.score(X, y), 1.)
#
@@ -808,7 +808,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# y[n_samples:2*n_samples] = 1
# y[2*n_samples:] = 2
# views_ind = np.array([0, 2, 4, 6])
- # clf = MuCumboClassifier(n_estimators=3)
+ # clf = MuComboClassifier(n_estimators=3)
# clf.fit(X, y, views_ind)
# assert_equal(clf.score(X, y), 1.)
#
@@ -830,13 +830,13 @@ class TestMuCumboClassifier(unittest.TestCase):
# y[n_samples:2*n_samples] = 1
# y[2*n_samples:] = 2
# views_ind = np.array([0, 2, 4, 6])
- # clf = MuCumboClassifier(n_estimators=4)
+ # clf = MuComboClassifier(n_estimators=4)
# clf.fit(X, y, views_ind)
# assert_equal(clf.score(X, y), 1.)
#
def test_classifier(self):
- return check_estimator(MuCumboClassifier)
+ return check_estimator(MuComboClassifier)
#
#
# def test_iris():
@@ -847,7 +847,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# classes = np.unique(iris.target)
#
# for views_ind in [iris.views_ind, np.array([[0, 2], [1, 3]])]:
- # clf = MuCumboClassifier(n_estimators=n_estimators)
+ # clf = MuComboClassifier(n_estimators=n_estimators)
#
# clf.fit(iris.data, iris.target, views_ind)
#
@@ -884,7 +884,7 @@ class TestMuCumboClassifier(unittest.TestCase):
#
for X, y, views_ind in data:
- clf = MuCumboClassifier(n_estimators=n_estimators, random_state=seed)
+ clf = MuComboClassifier(n_estimators=n_estimators, random_state=seed)
clf.fit(X, y, views_ind)
staged_dec_func = [dec_f for dec_f in clf.staged_decision_function(X)]
staged_predict = [predict for predict in clf.staged_predict(X)]
@@ -897,7 +897,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# assert_equal(len(staged_score), n_estimators)
#
# for ind in range(n_estimators):
- # clf = MuCumboClassifier(n_estimators=ind+1, random_state=seed)
+ # clf = MuComboClassifier(n_estimators=ind+1, random_state=seed)
# clf.fit(X, y, views_ind)
# dec_func = clf.decision_function(X)
# predict = clf.predict(X)
@@ -911,7 +911,7 @@ class TestMuCumboClassifier(unittest.TestCase):
# np.random.seed(seed)
#
# # Check that base trees can be grid-searched.
- mumbo = MuCumboClassifier(base_estimator=DecisionTreeClassifier())
+ mumbo = MuComboClassifier(base_estimator=DecisionTreeClassifier())
parameters = {'n_estimators': (1, 2),
'base_estimator__max_depth': (1, 2)}
clf = GridSearchCV(mumbo, parameters)
@@ -929,7 +929,7 @@ class TestMuCumboClassifier(unittest.TestCase):
#
# # Check pickability.
#
- # clf = MuCumboClassifier()
+ # clf = MuComboClassifier()
# clf.fit(iris.data, iris.target, iris.views_ind)
# score = clf.score(iris.data, iris.target)
# dump = pickle.dumps(clf)
@@ -945,19 +945,19 @@ class TestMuCumboClassifier(unittest.TestCase):
#
""" Test different base estimators."""
n_estimators = 5
- clf = MuCumboClassifier(RandomForestClassifier(), n_estimators=n_estimators)
+ clf = MuComboClassifier(RandomForestClassifier(), n_estimators=n_estimators)
clf.fit(self.iris.data, self.iris.target, self.iris.views_ind)
score = clf.score(self.iris.data, self.iris.target)
self.assertGreater(score, 0.95, "Failed with score = {}".format(score))
- clf = MuCumboClassifier(SVC(), n_estimators=n_estimators)
+ clf = MuComboClassifier(SVC(), n_estimators=n_estimators)
clf.fit(self.iris.data, self.iris.target, self.iris.views_ind)
score = clf.score(self.iris.data, self.iris.target)
self.assertGreater(score, 0.95, "Failed with score = {}".format(score))
# # Check that using a base estimator that doesn't support sample_weight
# # raises an error.
- clf = MuCumboClassifier(Lasso())
+ clf = MuComboClassifier(Lasso())
self.assertRaises(ValueError, clf.fit, self.iris.data, self.iris.target, self.iris.views_ind)
# assert_raises(ValueError, clf.fit, iris.data, iris.target, iris.views_ind)
#
@@ -985,13 +985,13 @@ class TestMuCumboClassifier(unittest.TestCase):
# for views_ind in (iris.views_ind, np.array([[0, 2], [1, 3]])):
# X_sparse = sparse_format(X_dense)
#
- # clf_sparse = MuCumboClassifier(
+ # clf_sparse = MuComboClassifier(
# base_estimator=CustomSVC(),
# random_state=seed,
# n_estimators=n_estimators)
# clf_sparse.fit(X_sparse, y, views_ind)
#
- # clf_dense = MuCumboClassifier(
+ # clf_dense = MuComboClassifier(
# base_estimator=CustomSVC(),
# random_state=seed,
# n_estimators=n_estimators)
@@ -1032,5 +1032,5 @@ class TestMuCumboClassifier(unittest.TestCase):
if __name__ == '__main__':
unittest.main()
# suite = unittest.TestLoader().loadTestsFromTestCase
- # (TestMuCumboClassifier().test_class_variation())
+ # (TestMuComboClassifier().test_class_variation())
# unittest.TextTestRunner(verbosity=2).run(suite)
\ No newline at end of file
diff --git a/multimodal/tests/test_data_sample.py b/multimodal/tests/test_data_sample.py
index 47a5754..469ba50 100644
--- a/multimodal/tests/test_data_sample.py
+++ b/multimodal/tests/test_data_sample.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
diff --git a/multimodal/tests/test_mkl.py b/multimodal/tests/test_mkl.py
index e1c147f..b384db4 100644
--- a/multimodal/tests/test_mkl.py
+++ b/multimodal/tests/test_mkl.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
diff --git a/multimodal/tests/test_mumbo.py b/multimodal/tests/test_mumbo.py
index 486045d..38f846c 100644
--- a/multimodal/tests/test_mumbo.py
+++ b/multimodal/tests/test_mumbo.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
diff --git a/multimodal/tests/test_mvml.py b/multimodal/tests/test_mvml.py
index 30da4a9..9f33c3b 100644
--- a/multimodal/tests/test_mvml.py
+++ b/multimodal/tests/test_mvml.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
diff --git a/setup.py b/setup.py
index 541026e..fa4dd7e 100644
--- a/setup.py
+++ b/setup.py
@@ -24,7 +24,7 @@
# -----------
#
# The multimodal package implement classifiers multiview,
-# MumboClassifier class, MuCumboClassifier class, MVML class, MKL class.
+# MumboClassifier class, MuComboClassifier class, MVML class, MKL class.
# compatible with sklearn
#
# Version:
--
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