In [1]:

    

from sklearn import tree
from dtreeviz.trees import *
from sklearn.datasets import load_boston

boston = load_boston()

X_train = boston.data
y_train = boston.target
testX = X_train[5,:]

regr = tree.DecisionTreeRegressor(max_depth=3)
regr = regr.fit(X_train, y_train)

viz = dtreeviz(regr, X_train, y_train, target_name='price',
               feature_names=boston.feature_names,
               X = testX)
viz


    

    
Out[1]: