首页>
外文OA文献
>Minimum description length criterion for modeling of chaotic attractors with multilayer perceptron networks
【2h】
Minimum description length criterion for modeling of chaotic attractors with multilayer perceptron networks
展开▼
机译:具有多层感知器网络的混沌吸引子建模的最小描述长度准则
展开▼
免费
页面导航
摘要
著录项
相似文献
相关主题
摘要
Overfitting has long been recognized as a problem endemic to models with a large number of parameters. The usual method of avoiding this problem in neural networks is to avoid fitting the data too precisely, and this technique cannot determine the exact model size directly. In this paper, we describe an alternative, information theoretic criterion to determine the number of neurons in the optimal model. When applied to the time series prediction problem we find that models which minimize the description length (DL) of the data, both generalize well and accurately capture the underlying dynamics. We illustrate our method with several computational and experimental examples.
展开▼