The preoccupation with test error in applied machine learning by Patrick Hall via +O'Reilly - "The technology exists now, be it purchased or built in-house, to directly measure the monetary value that a machine model is generating. This monetary value should be the criterion for selecting and deploying a commercial machine learning model, not its performance on old, static test data sets."
Great article.
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