In [2]:

    

# DictionaryLearning attempts to take a dataset and transform
# it into a sparse representation for classification.
# The features are a basis for the resulting datasets.


    

In [3]:

    

from sklearn.datasets import load_iris


    

In [4]:

    

from sklearn.decomposition import DictionaryLearning


    

In [5]:

    

iris = load_iris()


    

In [6]:

    

iris_data = iris.data


    

In [7]:

    

iris_target = iris.target


    

In [8]:

    

dl = DictionaryLearning(3)


    

In [9]:

    

transformed = dl.fit_transform(iris_data[::2])


    

In [10]:

    

transformed[:5]


    

    
Out[10]:





array([[ 0.        ,  6.34476574,  0.        ],
       [ 0.        ,  5.83576461,  0.        ],
       [ 0.        ,  6.32038375,  0.        ],
       [ 0.        ,  5.89318572,  0.        ],
       [ 0.        ,  5.45222715,  0.        ]])

In [11]:

    

transformed = dl.transform(iris_data[1::2])


    

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