本文介绍了Logm回归/二项式的glmnet错误的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
当尝试为family ="binomial"拟合glmnet()时，为Logistic回归拟合而出现此错误:
I get this error when trying to fit glmnet() with family="binomial", for Logistic Regression fit:
> data <- read.csv("DAFMM_HE16_matrix.csv", header=F)
> x <- as.data.frame(data[,1:3])
> x <- model.matrix(~.,data=x)
> y <- data[,4]
> train=sample(1:dim(x)[1],287,replace=FALSE)
> xTrain=x[train,]
> xTest=x[-train,]
> yTrain=y[train]
> yTest=y[-train]
> fit = glmnet(xTrain,yTrain,family="binomial")
Error in lognet(x, is.sparse, ix, jx, y, weights, offset, alpha, nobs, :
one multinomial or binomial class has 1 or 0 observations; not allowed
任何帮助将不胜感激-我已经搜索了互联网，却找不到任何有帮助的东西
Any help would be greatly appreciated - I've searched the internet and haven't been able to find anything that helps
数据如下:
> data
V1 V2 V3 V4
1 34927.00 156.60 20321 -12.60
2 34800.00 156.60 19811 -18.68
3 29255.00 156.60 19068 7.50
4 25787.00 156.60 19608 6.16
5 27809.00 156.60 24863 -0.87
...
356 26495.00 12973.43 11802 6.35
357 26595.00 12973.43 11802 14.28
358 26574.00 12973.43 11802 3.98
359 25343.00 14116.18 11802 -2.05
推荐答案
我认为这是由于因子变量的级别所致.假设有10个级别，而您的1个级别只有一个记录，请尝试删除此级别.您可以使用gdata包中的下降级别.
I think it is because of the levels of your factor variable. Suppose there are 10 levels and your 1 level has only one record, try to remove this level. You can use drop levels from gdata package.
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