How to plot a regression tree in Python

Question

So, first of all, I'm relatively new to Python so I'm not sure how to achieve my task. I was following an online tutorial on how to plot a decision tree using the Iris dataset (for classification). However, I'm trying to plot a single tree from regression.

Here's a snip of the data I'm using:

Here's the code I was using:

# Import Libraries and Load Data
import pandas as pd 
data = pd.read_csv("/Users/.../Desktop/cars_test.csv") 
import matplotlib.pyplot as plt
import numpy as np
cars = data

# Model
from sklearn.ensemble import RandomForestRegressor
model = RandomForestRegressor(n_estimators=10)

# Train
model.fit(cars.data, cars.target)

# Extract single tree for analysis
estimator = model.estimators_[5]

However, I'm getting an error that I'm not sure how to fix... The error I'm getting is:

AttributeError                            Traceback (most recent call
last) <ipython-input-27-37164305d7fe> in <module>()
     10 
     11 # Train
---> 12 model.fit(cars.data, cars.target)
     13 
     14 # Extract single tree for analysis

~/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py in
__getattr__(self, name)    4370             if self._info_axis._can_hold_identifiers_and_holds_name(name):    4371   
return self[name]
-> 4372             return object.__getattribute__(self, name)    4373     4374     def __setattr__(self, name, value):

AttributeError: 'DataFrame' object has no attribute 'data'

Any suggestions as to what I'm doing wrong?

Andrew Guy · Accepted Answer · 2019-05-06 07:17:01Z

1

You need to adapt the code to deal with your own data (note that the DataFrame you loaded doesn't have attributes for target or data). This means extracting the matrix of input data (X) and response variable (y) from your original dataset. I'm making a few assumptions here, but you can adapt accordingly.

# Import Libraries and Load Data
import pandas as pd 
data = pd.read_csv("/Users/.../Desktop/cars_test.csv") 
import matplotlib.pyplot as plt
import numpy as np
cars = data

# Model
from sklearn.ensemble import RandomForestRegressor
model = RandomForestRegressor(n_estimators=10)

X = cars.loc[:, cars.columns != 'th_km_per_year'].values
y = cars['th_km_per_year'].values

# Train
model.fit(X, y)

# Extract single tree for analysis
estimator = model.estimators_[5]

answered May 6, 2019 at 7:17

Andrew Guy

10.1k3 gold badges30 silver badges42 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

How to plot a regression tree in Python

1 Answer 1

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Your Answer

Sign up or log in

Post as a guest

Related