Day 9

When does normalization of features help?

Algorithms like KNN which depend on the distance metrics must be given normalized features.

Features should be normalized when using Tree Algorithms or Random Forest as it helps in faster convergence.

Models using Gradient Descent Approaches need scaled features to converge faster.

Both (A) & (C)

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Normalizing the features is beneficial in cases of Distance measurements and gradient descent methods.

Normalized features make each feature contribute approximately equally to the distance computations and solver converges faster when the features are scaled.

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Day 9

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Day 9

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