How can feature scaling affect the performance of certain Machine Learning algorithms?

  • It changes the distribution of the data
  • It helps algorithms converge faster and perform better
  • It increases the computational complexity of the model
  • It increases the number of features
Feature scaling normalizes or standardizes the features, making them all on a similar scale. This can help gradient descent-based algorithms converge faster and may lead to better performance for distance-based algorithms like KNN.
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