Supervised Learning: Algorithms and Business Use Cases II

This lesson continues to discuss supervised learning algorithms.

Decision trees

These are highly interpretable models that can be used for both classification and regression tasks. They split data-feature values into branches at decision nodes (e.g, if a feature is a color, each possible color becomes a new branch) until a final decision output is made. Decision trees are often fast and accurate and, hence, are widely used.

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