(Part 6 (of 11) of the Top 10 Data Mining Mistakes, drawn from the Handbook of Statistical Analysis and Data Mining Applications) -John Elder (email@example.com) I often evaluate promising investment systems, for possible implementation. In one, a Ph.D. consultant, with a couple of books under his belt, had prepared a neural network model for a Chicago bank to forecast interest rate changes. The model was 95% accurate – astonishing given the importance of such rates for much of the economy. The bank board was cautiously ecstatic, and sought a second opinion. My colleagues found that a version of the output
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