赤池信息量准则（英语：Akaike information criterion，简称AIC）是评估统计模型的复杂度和衡量统计模型「拟合」数据之优良性（英语：Goodness of Fit，白话：合身的程度）的一种标准，是由日本统计学家赤池弘次创立和发展的。赤池信息量准则创建在信息熵的概念基础上。
英语百科
Akaike information criterion 赤池信息量准则
The Akaike information criterion (AIC) is a measure of the relative quality of statistical models for a given set of data. Given a collection of models for the data, AIC estimates the quality of each model, relative to each of the other models. Hence, AIC provides a means for model selection.