Question: For a machine learning algorithm prone to overfitting due to a large number of features, how does the algorithm's performance change as the dimensionality of
For a machine learning algorithm prone to overfitting due to a large number of features, how does the algorithm's performance change as the dimensionality of the feature space increases?
Enhanced computational efficiency
Reduced overfitting
Improved generalization
Increased risk of overfitting
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