Decision Tree Visualizer
Build, visualize, and make predictions with intelligent decision trees
from sklearn.tree import DecisionTreeClassifier
model = DecisionTreeClassifier(random_state=42)
model.fit(X_train, y_train)
# Visualize the decision boundary
model = DecisionTreeClassifier(random_state=42)
model.fit(X_train, y_train)
# Visualize the decision boundary
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Build Decision Tree
The Iris dataset contains 3 classes of 50 instances each, where each class refers to a type of iris plant.
Make Prediction
Enter values for the features below to make a prediction:
Build a model first to enable predictions
Decision Tree Visualization
No Tree Built Yet
Build a decision tree using the panel on the left to see the visualization here.
Once built, you can zoom and pan to explore the tree structure.