Feature Scaling and Data Normalization Quiz

To normalize the range of independent variables

To ensure that each feature contributes approximately proportionately to the final distance (correct)

To make gradient descent converge faster

To facilitate the use of regularization in the loss function

Because it reduces the number of iterations needed

Because it standardizes the range of input feature values (correct)

Because it reduces the computational complexity of the algorithm

Because it reduces the likelihood of getting stuck in local minima

It could dominate the calculation of the Euclidean distance (correct)

It could cause the algorithm to underfit the data

It could cause the algorithm to overfit the data

It could prevent the algorithm from converging

<p>Because it ensures that the coefficient of each feature is properly regularized</p> Signup and view all the answers

<p>During the data preprocessing step</p> Signup and view all the answers