Update package to the newest scikit-learn version

Update of the package to the newest scikit-learn version 0.21.2 that
requires the MultiOutputMixin base class to ensure compatibility with
the scikit-learn pipeline.
	modified:   mbpls/__init__.py
	modified:   mbpls/mbpls.py
	modified:   setup.py

mbpls/__init__.py

@@ -22,4 +22,4 @@
 
 __all__ = ["mbpls", "data"]
 
-__version__ = "1.0.1"
+__version__ = "1.0.2"

mbpls/mbpls.py

@@ -7,7 +7,7 @@
 # License: 3-clause BSD
 
 
-from sklearn.base import BaseEstimator, RegressorMixin, TransformerMixin
+from sklearn.base import BaseEstimator, RegressorMixin, TransformerMixin, MultiOutputMixin
 from sklearn.utils.validation import check_X_y, check_array, check_is_fitted, check_consistent_length
 from sklearn import metrics
 import numpy as np
@@ -18,7 +18,7 @@
 __all__ = ['MBPLS']
 
 
-class MBPLS(BaseEstimator, TransformerMixin, RegressorMixin):
+class MBPLS(BaseEstimator, TransformerMixin, RegressorMixin, MultiOutputMixin):
     """(Multiblock) PLS regression for predictive modelling using latent variables
         --------------------------------------------------------------------------
         

setup.py

@@ -22,7 +22,7 @@
 # This is the lowest tested version. Below might work as well
 NUMPY_MIN_VERSION = '1.13.3'
 SCIPY_MIN_VERSION = '1.0.0'
-SCIKIT_LEARN_MIN_VERSION = '0.20.0'
+SCIKIT_LEARN_MIN_VERSION = '0.21.2'
 PANDAS_MIN_VERSION = '0.20.0'
 
 def setup_package():