Reducing Overfitting in ML Models

MediumMachine Learning00:00

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Your question is Reducing Overfitting in ML Models. Take a moment with it on the right.

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Problem

You are training a supervised learning model and the training score is much better than the validation score. The model looks strong in development, but it may not generalize well to new data.

Question

How would you handle overfitting in a machine learning model?

What to Look For

Large gap between training and validation performance
Validation score drops as model complexity increases
Instability across cross-validation folds
Sensitivity to noisy or high-cardinality features