Question: In the Universal Bank data in this chapter, only 10% of the records represented customers who had taken out a personal loan ( target variable).
In the Universal Bank data in this chapter, only 10% of the records represented customers who had taken out a personal loan ( target variable). If we were to score a new customer based upon the attributes we used in the algorhytm we would be accurate in the prediction about 90% of the time if we always scored the indivual as "not accepting a personal loan" because that indeed is what customers have done in the past. Why not accept being correct 90% of the time with this very simple decision rule?
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