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- W2146965232 abstract "We propose a spectral technique for analysing intermediate feature space of multiple classifier decisions, which enables a separable subset of patterns to be extracted. The method is applied to finding a set of patterns that are inconsistently classified, a random subset of which is left out of the training set of each expert in a multiple classifier framework." @default.
- W2146965232 created "2016-06-24" @default.
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- W2146965232 date "2003-01-22" @default.
- W2146965232 modified "2023-09-26" @default.
- W2146965232 title "Spectral partitioning for boundary estimation" @default.
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- W2146965232 doi "https://doi.org/10.1109/ijcnn.1999.836058" @default.
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