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In the context of decision trees, what does a higher cp value indicate?

  1. A more complex tree

  2. A less complex tree

  3. No effect on tree complexity

  4. Increased predictive accuracy

The correct answer is: A less complex tree

In the context of decision trees, a higher cp value, known as the complexity parameter, indicates a less complex tree. The cp value serves as a penalty for the number of splits in the tree: as this value increases, it restricts the tree from growing too complex. Essentially, when the cp value is set to a higher level, the tree will tend to be pruned more aggressively, leading to fewer branches and splits, which simplifies the model. This relationship between cp and tree complexity is crucial because a simpler tree often helps to mitigate overfitting, allowing the model to generalize better to unseen data. Therefore, selecting an appropriate cp value is an important step in building a decision tree that balances bias and variance, ultimately aiming for optimal predictive performance.