Title: Decision Tree Classifier
Slug: decision_tree_classifier
Summary: Training a decision tree classifier in scikit-learn.
Date: 2017-09-19 12:00
Category: Machine Learning
Tags: Trees And Forests
Authors: Chris Albon

Preliminaries



In [1]:

    
# Load libraries
from sklearn.tree import DecisionTreeClassifier
from sklearn import datasets

Load Iris Dataset



In [2]:

    
# Load data
iris = datasets.load_iris()
X = iris.data
y = iris.target

Create Decision Tree Using Gini Impurity



In [3]:

    
# Create decision tree classifer object using gini
clf = DecisionTreeClassifier(criterion='gini', random_state=0)

Train Model



In [4]:

    
# Train model
model = clf.fit(X, y)

Create Observation To Predict



In [5]:

    
# Make new observation
observation = [[ 5,  4,  3,  2]]

Predict Observation



In [6]:

    
# Predict observation's class    
model.predict(observation)









    Out[6]:





array([1])

View Predicted Probabilities



In [7]:

    
# View predicted class probabilities for the three classes
model.predict_proba(observation)









    Out[7]:





array([[ 0.,  1.,  0.]])