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Error bounds based on worst likely assignments use permutation tests tovalidate classifiers. Worst likely assignments can produce effective boundseven for data sets with 100 or fewer training examples. This paper introduces astatistic for use in the permutation tests of worst likely assignments thatimproves error bounds, especially for accurate classifiers, which are typicallythe classifiers of interest.

Improved Error Bounds Based on Worst Likely Assignments