为什么在 R 中的 glm 函数中可以只传递 1 列给 glmnet？

Question

为什么在 glmnet 包中的 glmnet 函数中不可能仅将 1 个解释变量传递给模型，而在基础中的 glm 函数中是可能的？代码和错误如下：

> 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")

Answer 1

因为文档是这么说的。

For family="binomial" should be either a factor with two levels, or a two-column matrix of counts or proportions (the second column is treated as the target class; for a factor, the last level in alphabetical order is the target class).

你有两个选择。要么构建一个矩阵，其中两列代表计数，要么将 x 转换为具有两个水平的因子。

Answer 2

我不知道为什么，但这是某种内部限制。这与罗曼上面所说的家庭无关。

glmnet(x = as.matrix(iris[2:4]), y = as.matrix(iris[1]))
## long output
glmnet(x = as.matrix(iris[1]), y = as.matrix(iris[1]))
Error in glmnet(x = as.matrix(iris[2]), y = as.matrix(iris[1])) : 
  x should be a matrix with 2 or more columns

在代码中简单检查一下https://github.com/cran/glmnet/blob/master/R/glmnet.R#L20

Answer 3

这是我从包的维护者 (Trevor Hastie) 那里得到的这个问题的答案：

glmnet is designed to select variables from a (large) collection. Allowing for 1 variable would have created a lot of edge case programming, and I was not interested in doing that. Sorry!

为什么在 R 中的 glm 函数中可以只传递 1 列给 glmnet？

Why can't pass only 1 coulmn to glmnet when it is possible in glm function in R?

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