gistfile1.txt

dtree = DecisionTreeClassifier(max_depth = 4)
dtree.fit(data_data, data_target)
scores = cross_validation.cross_val_score(dtree, data_data, data_target, cv=10)
print scores
print dtree.score(data_data, data_target)

from StringIO import StringIO
from inspect import getmembers
out = StringIO()
out = tree.export_graphviz(dtree, feature_names=names_of_attributes, out_file='tree_data.dot')