In [1]:

    

from tpot import TPOT
from sklearn.datasets import load_digits
from sklearn.cross_validation import train_test_split


    

In [2]:

    

digits = load_digits()
X_train, X_test, y_train, y_test = train_test_split(digits.data, digits.target,
                                                    train_size=0.75, test_size=0.25)
X_train.shape, X_test.shape, y_train.shape, y_test.shape


    

    
Out[2]:





((1347, 64), (450, 64), (1347,), (450,))

In [3]:

    

tpot = TPOT(generations=5)
tpot.fit(X_train, y_train)
print(tpot.score(X_test, y_test))


    

    




0.968636234802

In [4]:

    

tpot.export('tpot_mnist_pipeline.py')


    

In [ ]: