Plot_DT_Tree

from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier, plot_tree
import matplotlib.pyplot as plt

# Load the Iris dataset as an example
iris = load_iris()
X, y = iris.data, iris.target

# Create a decision tree classifier
clf = DecisionTreeClassifier(random_state=42)
clf.fit(X, y)

# Plot the decision tree
plt.figure(figsize=(12, 8))
plot_tree(clf, feature_names=iris.feature_names, class_names=iris.target_names, filled=True, rounded=True)
plt.show()