In [1]:
# write out some toy data
from sklearn.datasets import load_digits
import cPickle
digits = load_digits()
X, y = digits.data, digits.target
for i in range(10):
cPickle.dump((X[i::10], y[i::10]), open("data/batch_%02d.pickle" % i, "w"), -1)
In [2]:
from sklearn.linear_model import SGDClassifier
In [3]:
sgd = SGDClassifier()
for i in range(9):
X_batch, y_batch = cPickle.load(open("data/batch_%02d.pickle" % i))
sgd.partial_fit(X_batch, y_batch, classes=range(10))
In [4]:
X_test, y_test = cPickle.load(open("data/batch_09.pickle"))
sgd.score(X_test, y_test)
Out[4]:
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