The 12 ways to screw up your predictive analytics project
Whether you’re new to predictive analytics or have a few projects under your belt, it’s all too easy to make gaffes. “The vast majority of analytic projects are riddled with mistakes,” says John Elder, CEO at data mining firm Elder Research.
Most of those aren’t fatal — almost every model can be improved — but many projects fail miserably nonetheless, leaving the business with a costly investment in software and time, and nothing to show for it.
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