如何使用sklearn在Logistic回归模型中查找beta值 [英] How to find beta values in Logistic Regression model with sklearn

问题描述

基于Logistic回归函数:

Based on the Logistic Regression function:

我正在尝试从 scikit-learn 中的模型中提取以下值.

I'm trying to extract the following values from my model in scikit-learn.

和

其中是截距，而是回归系数. (根据维基百科)

Where is the intercept and is the regression coefficient. (as per the wikipedia)

现在，我认为我可以通过执行model.intercept_来获取，但我一直在努力获取.有什么想法吗?

Now, I think I can get by doing model.intercept_ but I've been struggling to get . Any ideas?

推荐答案

您可以使用model.coef_访问特征的系数.

You can access the coefficient of the features using model.coef_.

它给出了与值beta1，beta2等对应的值列表.列表的大小取决于您的逻辑回归使用的解释变量的数量.

It gives a list of values that corresponds to the values beta1, beta2 and so on. The size of the list depends on the amount of explanatory variables your logistic regression uses.

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