Which is better forward or backward selection?
The backward method is generally the preferred method, because the forward method produces so-called suppressor effects. These suppressor effects occur when predictors are only significant when another predictor is held constant.
What is the difference between forward selection and backward selection in terms of feature selection?
Forward selection starts with a (usually empty) set of variables and adds variables to it, until some stop- ping criterion is met. Similarly, backward selection starts with a (usually complete) set of variables and then excludes variables from that set, again, until some stopping criterion is met.
How is forward selection different from backward selection?
This is because forward selection starts with a null model (with no predictors) and proceeds to add variables one at a time, and so unlike backward selection, it DOES NOT have to consider the full model (which includes all the predictors). In fact, it will only consider models with number of variables less than:
Why do forward and backward give you different models?
Even if you have the same number of terms in the final model, forward and backward can give you a different model. It’s all a matter of the statistic (often an F statistic) used in the step wise process. Thanks for contributing an answer to Cross Validated!
What is the starting model in R-forward-backward?
The stepAIC function automatically prints each step of the selection process in the console and it seems like the selection starts with the full model. However, based on the answer of jjet I am not sure if I have done anything wrong. I believe “forward-backward” selection is another name for “forward-stepwise” selection.
Can a forward and backward regression give the same result?
Yes, in general, forward and backward step wise regression can give you the same result, but there is not a requirement that such a result be the case. Even if you have the same number of terms in the final model, forward and backward can give you a different model. It’s all a matter of the statistic (often an F statistic)…
https://www.youtube.com/watch?v=-inJu1jHqb8