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Decision Tree is preferred over Random Forest when interpretability is important.
Decision Tree is easier to interpret and visualize than Random Forest.
Decision Tree is better suited for small datasets with few features.
Random Forest is better suited for large datasets with many features.
Random Forest is less prone to overfitting than Decision Tree.
Decision Tree can be used as a building block for Random Forest.
If inter...
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