赤池信息标准

Dictionary of Bioinformatics and Computational Biology Pub Date : 2014-04-07 DOI:10.1002/9780471650126.DOB0802

P. Larrañaga, C. Bielza

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引用次数: 162

摘要

赤池信息准则是在不同类型的模型之间进行选择的一系列方法之一，这些方法在拟合优度和模型复杂性之间寻求适当的权衡。如果选择参数以优化拟合优度，则模型越复杂，其拟合优度通常越好，但这并不一定使其成为识别新数据可能表现的整体“更好”模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Akaike Information Criterion

The Akaike Information Criterion is one of a range of ways of choosing between different types of models that seek an appropriate trade-off between goodness of fit and model complexity. The more complicated a model is the better generally will be its apparent goodness of fit, if the parameters are selected to optimise goodness of fit, but this does not necessarily make it a ‘better’ model overall for identifying how new data might behave.

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Dictionary of Bioinformatics and Computational Biology

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