Evaluating the performance of a classifier: n-fold cross validation

D1

D2

D3

Dn

Run 1

Run 2

Run 3

Run n

• Partition the data set in n segments

• Do n times

  • Train the classifier with the green segments
  • Test accuracy on the red segments

• Compute statistics on the n runs

  • Variance
  • Mean accuracy

• Accuracy: on test data of size m

  • Acc =

Original data set

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