Forward selection is a regression which begins with an empty model and adds variable one by one. In each step, we add the one variable that gives the single best improvement to your model.
Continue reading “Forward Selection”Month: July 2020
Statistical Significance
Imagine you are doing a coin toss. You assume that the coin is a fair coin which has two sides: a picture and a number. When you do the first toss, what appears is the picture. In this stage you feel everything is normal. The probability for the number side and the picture side are same: 0.5.
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