人工智能
人工神经网络
计算机科学
一般化
残余物
机器学习
模式识别(心理学)
数学
算法
数学分析
作者
Lars Kai Hansen,Peter Salamon
摘要
Several means for improving the performance and training of neural networks for classification are proposed. Crossvalidation is used as a tool for optimizing network parameters and architecture. It is shown that the remaining residual generalization error can be reduced by invoking ensembles of similar networks.< >
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