为什么在R中的glm功能可能的情况下不能仅将1个指令传递给glmnet?

问题描述

为什么从glmnet包中的glmnet函数中不能仅将一个解释变量传递给glmnet函数中的模型?代码和错误如下:

Why there is no possibility to pass only 1 explanatory variable to model in glmnet function from glmnet package when it is possible in glm function from base?Code and error are below:

> modelX<-glm( ifelse(train$cliks <1,0,1)~(sparseYY[,40]), family="binomial")
> summary(modelX)

Call:
glm(formula = ifelse(train$cliks < 1, 0, 1) ~ (sparseYY[, 40]),
    family = "binomial")

Deviance Residuals:
    Min       1Q   Median       3Q      Max
-0.2076  -0.2076  -0.2076  -0.2076   2.8641

Coefficients:
               Estimate Std. Error  z value Pr(>|z|)
(Intercept)    -3.82627    0.00823 -464.896   <2e-16 ***
sparseYY[, 40] -0.25844    0.15962   -1.619    0.105
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 146326  on 709677  degrees of freedom
Residual deviance: 146323  on 709676  degrees of freedom
AIC: 146327

Number of Fisher Scoring iterations: 6

> modelY<-glmnet( y =ifelse(train$cliks <1,0,1), x =(sparseYY[,40]), family="binomial"  )
Błąd wif (is.null(np) | (np[2] <= 1)) stop("x should be a matrix with 2 or more columns")

推荐答案

这是我从软件包维护者(Trevor Hastie)那里得到的一个答案:

Here is an answer I got to this question from the maintainer of the package (Trevor Hastie):

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