什么是calibration

来自wiki
There are two main uses of the term calibration in statistics that denote special types of statistical inference problems. Thus "calibration" can mean
A reverse process to regression, where instead of a future dependent variable being predicted from known explanatory variables, a known observation of the dependent variables is used to predict a corresponding explanatory variable.[1]
逆回归
Procedures in statistical classification to determine class membership probabilities which assess the uncertainty of a given new observation belonging to each of the already established classes.
In addition, "calibration" is used in statistics with the usual general meaning of calibration. For example, model calibration can be also used to refer to Bayesian inference about the value of a model's parameters, given some data set, or more generally to any type of fitting of a statistical model.
统计分类，类别成员概率，给定的新观测属于已有的类别的概率。用来一般的意义的校准。比如模型叫尊也用于指贝叶斯推断，关于模型参数的。给定数据集，或更一般的任何类型的模型拟合。