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In n-fold cross-validation, each data point belongs to exactly one test fold, which makes the test folds independent. However, if the data in test folds $i$ and $j$ are independent, are the error estimates $e_i$ and $e_j$ on test folds $i$ and $j$ also independent ?

  1. True, because each test fold contains different data points.
  2. False, because data points can appear in multiple training sets, making error estimates dependent.
  3. True, because error estimates are calculated separately for each fold.
  4. None of these
     

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False. Since a data point appears in multiple folds the training sets are dependent and thus test fold error estimates are dependent.
 
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