How modeling choices affect machine learning predictions

All machine learning models make assumptions in order to learn statistical regularities from data. In order to trust the results of the machine learning analysis, it’s critical to assess how much the results depend on the initial assumptions made in the modeling process. Often, users are faced with assumptions which are qualitatively interchangeable: there is no reason to prefer one assumption over another, given prior beliefs. In these cases, large discrepancy in the results due to switching between assumptions is …

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