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Use of bootstrap samples in quadratic classifier design

We propose to use bootstrap samples in designing an extended quadratic classifier. The proposed method is to generate bootstrap samples which have much information about distributions, and to optimise the extended quadratic classifier so that the error estimated by using bootstrap samples is minimized. The performance of the proposed classifier is demonstrated on real data.