Mastering Machine Learning with R(Second Edition)
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Evaluation

With the evaluation process, the main goal is to confirm that the model selected at this point meets the business objective. Ask yourself and others, "Have we achieved our definition of success?". Let the Netflix prize serve as a cautionary tale here. I'm sure you are aware that Netflix awarded a $1-million prize to the team that could produce the best recommendation algorithm as defined by the lowest RMSE. However, Netflix did not implement it because the incremental accuracy gained was not worth the engineering effort! Always apply Occam's razor. At any rate, here are the tasks:

  1. Evaluating the results.
  2. Reviewing the process.
  3. Determining the next steps.

In reviewing the process, it may be necessary, as you no doubt determined earlier in the process, to take the results through governance and communicate with the other stakeholders in order to gain their buy-in. As for the next steps, if you want to be a change agent, make sure that you answer the what, so what, and now what in the stakeholders' minds. If you can tie their now what into the decision that you made earlier, you have earned your money.