Issue No. 04 - April (1997 vol. 19)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.588027
<p><b>Abstract</b>—This paper presents a method for combining classifiers that uses estimates of each individual classifier's local accuracy in small regions of feature space surrounding an unknown test sample. An empirical evaluation using five real data sets confirms the validity of our approach compared to some other Combination of Multiple Classifiers algorithms. We also suggest a methodology for determining the best mix of individual classifiers.</p>
Combination of classifiers, dynamic classifier selection, local classifier accuracy, classifier fusion, ROC analysis.
W. P. Kegelmeyer Jr., K. Woods and K. Bowyer, "Combination of Multiple Classifiers Using Local Accuracy Estimates," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 19, no. , pp. 405-410, 1997.