By: Sam Koslowsky, Harte Hanks
Data miners employ a variety of techniques to develop robust predictive models. Often, our analysts are confronted with a dilemma. Should we construct one model to address the business objective? Or perhaps, multiple models may be in order? Take, for example, a marketer that has a presence on the east coast and in the mid-west. Will one analysis be sufficient, or conceivably splitting up the universe by geography, and then formulating separate models on each population would provide enhanced results. After all, behaviors in different parts of the country may very well be different. When is it appropriate
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