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ClassificationIntermediateDecision Tree

Decision Tree Classification

Builds a decision tree to classify breast cancer samples.

Key highlights

  • Trains/test split with accuracy
  • Exports human-readable tree rules
  • Predicts a new sample

Metrics

AccuracyTree rules

Dataset

Breast Cancer

View full codeDownload datasetView report

Outputs

Decision tree summary
Rules snapshot for classification

Code snapshot

Key lines that anchor the experiment workflow.

dt_classifier = DecisionTreeClassifier(random_state=42)
dt_classifier.fit(X_train, y_train)
print(export_text(dt_classifier))

Next steps

Want to explore further? Try the full gallery or open the raw script to tweak parameters.

Back to galleryOpen code on GitHub