I imported some data as follows
surv <- read.table("http://www.stat.ufl.edu/~aa/glm/data/Student_survey.dat",header = T)
x <- as.matrix(select(surv,-ab))
y <- as.matrix(select(surv,ab))
glmnet::cv.glmnet(x,y,alpha=1,,family="binomial",type.measure = "auc")
and I am getting the following error.
NAs introduced by coercion
Show Traceback
Error in lognet(x, is.sparse, ix, jx, y, weights, offset, alpha, nobs, : NA/NaN/Inf in foreign function call (arg 5)
What is a good fix for this?
The documentation of the glmnet package has the information that you need,
surv <- read.table("http://www.stat.ufl.edu/~aa/glm/data/Student_survey.dat", header = T, stringsAsFactors = T)
x <- surv[, -which(colnames(surv) == 'ab')] # remove the 'ab' column
y <- surv[, 'ab'] # the 'binomial' family takes a factor as input (too)
xfact = sapply(1:ncol(x), function(y) is.factor(x[, y])) # separate the factor from the numeric columns
xfactCols = model.matrix(~.-1, data = x[, xfact]) # one option is to build dummy variables from the factors (the other option is to convert to numeric)
xall = as.matrix(cbind(x[, !xfact], xfactCols)) # cbind() numeric and dummy columns
fit = glmnet::cv.glmnet(xall,y,alpha=1,family="binomial",type.measure = "auc") # run glmnet error free
str(fit)
List of 10
$ lambda : num [1:89] 0.222 0.202 0.184 0.168 0.153 ...
$ cvm : num [1:89] 1.12 1.11 1.1 1.07 1.04 ...
$ cvsd : num [1:89] 0.211 0.212 0.211 0.196 0.183 ...
$ cvup : num [1:89] 1.33 1.32 1.31 1.27 1.23 ...
$ cvlo : num [1:89] 0.908 0.9 0.89 0.874 0.862 ...
$ nzero : Named int [1:89] 0 2 2 3 3 3 4 4 5 6 ...
.....