Can Randomness be an Element in Multiple Regression (CTBEB)- Juniper Publishers
In some of the more recent literature and discussions, discussion has
ensued about the use of pure random or noise variables that end up as
key regression variables. In our big data environment with millions of
records and thousands of variables, intuitively one might think that
random or spurious variables might be a normal outcome in many models.
As a data miner, I am always intrigued by fellow colleagues who arrive
at certain findings based on their research and work. When considering
the validity of these comments, I harken back to my experience in
building hundreds of models over the years in a variety of different
industry sectors. Practitioners typically adopt techniques that ensure
the unlikelihood of these variables in any final regression equation.
These techniques will be discussed later on in this article.
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