Graphing Random Forest with Tree for Linear Regression

Question

I am having a problem graphing my linear regression model with a random forest. Also, I am having a problem defining my feature_names and class_names because it is a continuous number. In R, this is a fairly simple visual, but python seems to require a little more thought.

I am utilizing the NYC Property data to predict future housing prices. I want to visualize this in a decision tree.

python
from sklearn.ensemble import RandomForestRegressor
random_forest = RandomForestRegressor(n_estimators=12)
random_forest.fit(X_train, y_train)

from sklearn.tree import export_graphviz

estimator = random_forest.estimators_[5]

export_graphviz(
    estimator,
    out_file="nyc_tree.dot",
    rounded=True,
    filled=True
)

I expect a decision tree with several branches.

Answer 1

What kind of issue are you encountering? Making your data is not shaped the right way (n_samples,n_features) for X, and (n_samples) for y.

Otherwise, this website might help you, it's doing exactly what your looking for.