<jupyter_start><jupyter_text>parameter_data = simulations[simulations.columns[simulations.columns.to_series().str.contains('par|like1')]]features = list(parameter_data.columns[1:11])print("* features:", features, sep="\n")from sklearn.tree import DecisionTreeClassifier, export_graphviz,DecisionTreeRegressory = parameter_data["like1"]X = parameter_data[features]dt = DecisionTreeRegressor(min_samples_decrease=50, random_state=99,max_depth=6,criterion='mse')dt.fit(X, y)<jupyter_code>from sklearn.externals.six import StringIO  
from IPython.display import Image  
from sklearn.tree import export_graphviz
import pydotplus
dot_data = StringIO()
export_graphviz(dt, out_file=dot_data,  
                filled=True, rounded=True,
                special_characters=True)
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  
Image(graph.create_png())
from sklearn.externals.six import StringIO  
from IPython.display import Image  
from sklearn.tree import export_graphviz
import graphviz<jupyter_output><empty_output>
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