You are working with a logistic regression model to predict the probability that a user will click on an ad. Your model has hundreds of features, and you're not sure if all of those features are…

You are working with a logistic regression model to predict the probability that a user will click on an ad. Your model has hundreds of features, and you're not sure if all of those features are helping your prediction. Which regularization technique should you use to prune features that aren't contributing to the model?