Requirement $3.$ James has to present both models and the conclusions to the president of Keebler dash Olson. He knows that in the past the president has preferred using models based on full decision trees because they seem to fit the training data more closely. How should James explain the pruned decision tree$$ model?

James could approach this problem by explaining

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Using the full model

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risks overfitting the training data as the model may start fitting the noise of the data instead of the signal.

shows that the cross$-$validation sample contained outliers.

As$$ such, the model would perform

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poorly when applied to new data even though it seems to fit the training data more closely.

better when applied to new data as it seems to fit the training data closely.

Pruning

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helps reduce the risk of bias of the model.

increases the bias of the model.

Pruning also

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helps reduce the risk of overfitting.

increases the overfitting.