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Practical Predictive Analytics by Ralph Winters

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Model scoring

Model scoring makes the model actionable. If you develop a model and you are unable to apply the results to new data, then you will be unable to do any prediction on an ongoing basis. New model scoring often involves outputing the development model outputs to a real-time scoring engine. That engine is often Java or C++. How that is performed varies vastly depending upon the modeling technique. Sometimes the scoring is performed separately, so it can be optimized for efficiency.

Regression type models are relatively easy to score, since all that is needed are the model's coefficients and intercepts. Other types of models need a little more work. For example, decision tree software should be able to output a set of decision rules ...

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