Portions excerpted from Chapter 2 of his book Applied Predictive Analytics (Wiley 2014, http://amzn.com/1118727967)
Successful predictive modeling is more than identifying the right algorithms. And, even though 60-90% of our time is spend on data preparation before deploying the first predictive model built from a new data set, successful predictive modeling goes well beyond effective data cleaning and feature creation. I argue there, that most failed predictive modeling projects are on the path to failure before the first data set is even loaded because of these three steps that are frequently overlooked.
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