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Ridge regression helps to penalize features converting completely zero, on the other side Lasso tunes parameters making closer to zero but never equal.

True
False

Respuesta :

Talia2007

True, Ridge Regression is a technique for analyzing multiple regression data that suffer from multicollinearity. When multicollinearity occurs, least squares estimates are unbiased, but their variances are large so they may be far from the true value.
AmeliaJonlish

Answer:

True!

Explanation:

Ridge regression is a way to create a parsimonious model when the number of predictor variables in a set exceeds the number of observations, or when a data set has correlations between predictor variables.