如何使用多核处理更快地运行glm功能 [英] How can I use multi cores processing to run glm function faster

问题描述

我对r有点陌生，我想使用一个允许多核处理的包，以便更快地运行glm函数.我想知道是否有可以用于此问题的语法. 这是我编写的示例glm模型，可以添加将使用多核的参数吗?

I'm a bit new to r and I would like to use a package that allows multi cores processing in order to run glm function faster.I wonder If there is a syntax that I can use for this matter. Here is an example glm model that I wrote, can I add a parameter that will use multi cores ?

g<-glm(IsChurn~.,data=dat,family='binomial')

谢谢.

推荐答案

我使用speedglm，结果非常好:使用glm，我花了14.5秒获得结果，而使用speedglm，我花了1.5秒.改进了90％.代码非常简单:m <- speedglm(y ~ s1 + s2,data=df).只是不要忘记安装并调用该软件包.另一个问题:不能将所有变量都与."一起使用speedglm无法将点识别为所有变量".

I used speedglm and the results are very good: using glm it took me 14.5 seconds to get results and with speedglm it took me 1.5 sec. that a 90% improvement..the code is very simple: m <- speedglm(y ~ s1 + s2,data=df). Just don't forget to install and call the package. Another issue: you can't use all variables with "." the speedglm does not recognize the dot as "all variables".

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