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QUANTIFYING THE VALUE OF MODELS AND DATA: A COMPARISON OF THE PERFORMANCE OF REGRESSION AND NEURAL NETS WHEN DATA QUALITY VARIES
Under circumstances where data quality may vary, knowledge about the potential performance of alternate predictive models can enable a decision maker to design an information system whose value is optimized in two ways. The decision maker can select a model which is least sensitive to predictive
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