Which of the following is NOT a type of regularization technique used in linear regression to prevent overfitting?

Q.No 9. Regularization techniques in linear regression aim to:a) Improve the interpretability of the modelb) Reduce the variance of the model and prevent overfittingc) Increase the complexity of the modeld) Decrease the bias of the model

Which of the following are regularization techniques?

why regularisation improve overfitting

Which technique serves as a form of regularization by restricting the exploration of parameter space from the initial parameters, and requires validation data to determine its timing?*a) Lasso regressionb) Dropoutc) Early stoppingd) Ridge regression

Which of the following techniques can help prevent overfitting in regression models?