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- W1641893298 abstract "In this work we shall discuss how to apply classical input relevance results for linear Fisher discriminants to measure the relevance of the linear last hidden layer of a Non Linear Discriminant Analysis (NLDA) network. We shall quickly review first possible ways to extend classical and non linear Fisher analysis to multiclass problems and introduce a criterion function very well suited computationally to NLDA networks. After defining a relevance statistic for linear NLDA units, we shall numerically illustrate the resulting procedures on a synthetic 3 class classification problem." @default.
- W1641893298 created "2016-06-24" @default.
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- W1641893298 date "2003-01-01" @default.
- W1641893298 modified "2023-09-26" @default.
- W1641893298 title "Bootstrap for model selection: linear approximation of the optimism" @default.
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- W1641893298 doi "https://doi.org/10.1007/3-540-44868-3_24" @default.
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