I am trying to print out the decision tree for a forest from scikit-learn ensemble: For example for a DecisionTreeClassifier, I would use:
from sklearn import tree
clf = tree.DecisionTreeClassifier( criterion ='entropy', max_depth = 3,
min_samples_leaf =
clf = clf.fit( X_train, y_train) #Input this to analyze the training set.
import pydot, StringIO
dot_data = StringIO.StringIO()
tree.export_graphviz( clf, out_file = dot_data,
feature_names =[' age', 'sex', 'first_class', 'second_class', 'third_class'])
graph = pydot.graph_from_dot_data( dot_data.getvalue())
graph.write_png('visualtree.png')
from IPython.core.display import Image
Image( filename =visualtree.png')
I tried a similar approach for Random Forest Regressor (see below and got an error)
# Fit regression model
from sklearn.ensemble import RandomForestRegressor
rfr_1 = RandomForestRegressor(n_estimators=10, max_depth=5)
rfr_1.fit(X, y)
from sklearn.ensemble import*
import pydot, StringIO
dot_data = StringIO.StringIO()
ensemble.export_graphviz( rf1, out_file = dot_data,
feature_names =[' Temperature', 'Translator Bacteria'])
graph = pydot.graph_from_dot_data( dot_data.getvalue())
graph.write_png('fish.png')
from IPython.core.display import Image
Image( filename ='fish.png')
File "randomforestregressor.py", line 45, in
ensemble.export_graphviz( rf1, out_file = dot_data,
NameError: name 'ensemble' is not defined
How would I accomplish this? thanks!