RANK AND RESPONSE COMBINATION FROM CONFUSION MATRIX DATA
Date
2000-06-20
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Abstract
The use of prior behavior of a classifier, as measured by the
confusion matrix, can yield useful information for merging multiple
classifiers. In particular, response vectors can be estimated and a ranking of
possible classes can be produced which can allow Borda type reconciliation
methods to be applied. A combination of real data and the simulation of
multiple classifiers is used to evaluate this idea, and to compare with eleven
other classifier combination techniques. Millions of classifications were used
in the evaluation.
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Computer Science