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- W176971757 abstract "We propose a data reduction approach for flnding a reference set for the nearest neighbour classifler. The approach is based on classifler ensembles. Each ensemble member is given a subset of the training data. Using Wilson's editing method, the ensemble member produces a reduced reference set. We explored several routes to make use of these reference sets. The results with 10 real and artiflcial data sets indicated that merging the reference sets and subsequent editing of the merged set provides the best trade-ofi between the error and the size of the resultant reference set. This approach can also handle large data sets because only small fractions of the data are edited at a time." @default.
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- W176971757 date "2007-01-01" @default.
- W176971757 modified "2023-09-23" @default.
- W176971757 title "Data reduction using classifier ensembles." @default.
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