@harry wrote:
I am currently studying about forward stepwise selection and backward stepwise selection method for selection of the features in the model.
forward stepwise selection - It is the method which begins with a model containing no predictors and then adds predictors to the model,one-at-a-time until all of the predictors are in the model.
backward stepwise selection - it begins with the full least squares model containing all p predictors, and then iteratively removes the least useful predictor,one-at-a-time.
I want to know the reason why we can not use backward stepwise selection method when a number of the data point is less than the number of features in a data point.
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