工作示例来自www.example.com https://glmnet.stanford.edu/articles/glmnet.html#multinomial-regression-family-multinomial-:

data(MultinomialExample)
x <- MultinomialExample$x
y <- MultinomialExample$y
cvfit <- cv.glmnet(x, y, family = "multinomial")

cvfit返回：

Call:  cv.glmnet(x = x, y = y, family = "multinomial") 

Measure: Multinomial Deviance 

      Lambda Index Measure      SE Nonzero
min 0.009791    35   1.409 0.05611      14
1se 0.022619    26   1.455 0.04132       9

现在我想提取9个非零系数。不过：

sum(matrix(coef(cvfit)$'1') != 0)
sum(matrix(coef(cvfit)$'2') != 0)
sum(matrix(coef(cvfit)$'3') != 0)

返回10、12、10。此外：

length(Reduce(intersect, 
              list(rownames(coef(cvfit)$'1')[matrix(coef(cvfit)$'1') != 0], 
                   rownames(coef(cvfit)$'2')[matrix(coef(cvfit)$'2') != 0], 
                   rownames(coef(cvfit)$'3')[matrix(coef(cvfit)$'3') != 0])))

返回1.
对于lambda.1se，Nonzero = 9代表什么？当type.multinomial = "ungrouped"（当family = "multinomial"时默认设置为cv.glmnet()）时，我如何恢复这些变量名和相应的系数？
谢谢