How do you use DecisionTreeClassifier and visualize the decision tree using Scikit-learn s plot tree

Question

With the help of proper code can I know How do you use DecisionTreeClassifier and visualize the decision tree using Scikit-learn’s plot_tree?

Answer 1

You can train a DecisionTreeClassifier and visualize the tree using Scikit-learn’s plot_tree to interpret model decisions.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• DecisionTreeClassifier(max_depth=3) limits tree depth to improve interpretability.
• plot_tree() creates a visual representation of decision splits, showing feature names and class labels.
• filled=True colorizes nodes based on class, improving readability.
• feature_names and class_names add context to the tree structure.

Hence, visualizing decision trees helps understand feature importance and decision paths, making models more transparent and interpretable. Let me know if you’d like me to refine or add anything!