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Predictive Modeling
You will find Reduced Error Logistic Regression (RELR) especially beneficial and accurate in predictive modeling problems where other approaches fail. This includes problems with large numbers of variables and interactions, correlated variables, nonlinear variables, unbalanced samples, and/or small sample sizes. Please visit our Case Studies page for numerous examples of how RELR is being applied to more difficult predictive modeling problems.
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The effect of Reduced Error Logistic Regression is to increase your resolution dramatically like having a microscope, so you can see things that would not be possible otherwise.
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