# Predicting values for a Naive Bayes in R

I have the following data set and am trying to predict on the naive bayes values

1 12073402              b@hotmail.com         0        GOOD            \\0
2 12073514                 mo@cox.net         0        GOOD            \\0
3 12073541                v@yahoo.com         0   EXCELLENT            \\0
4 12073591              rob@yahoo.com         1   EXCELLENT           \001
5 12073653                c@ymail.com         0   EXCELLENT            \\0
6 12073768                r@yahoo.com         0   EXCELLENT            \\0

So I run the following command to run NB and to predict on the desired values.

m <- naiveBayes(buyer_returned ~ owns_home + credit_type, dat)
m

> predict(m, dat[1:10, -5])
Error in FUN(1:2[[2L]], ...) : subscript out of bounds
> predict(m, dat[1:10, -5], type="raw")
Error in FUN(1:2[[2L]], ...) : subscript out of bounds

> predict(m, dat[1:10, 5])
Error in log(sapply(attribs, function(v) { :
Non-numeric argument to mathematical function
> predict(m, dat[1:10, 5], type="raw")
Error in log(sapply(attribs, function(v) { :
Non-numeric argument to mathematical function

I'm not sure why I get the subscript out of bounds error. What is the issue.

Here's info that might be useful:

> str(dat)
'data.frame':   50000 obs. of  5 variables:
$lead_id : int 12073402 12073514 12073541 12073591 12073653 12073768 12073809 12073818 12073897 12073943 ...$ email         : Factor w/ 49755 levels "0011werbicki1100@gmail.com",..: 6231 32482 47424 38883 6784 37311 33483 37525 41427 35459 ...
$owns_home : int 0 0 0 1 0 0 0 0 0 0 ...$ credit_type   : Factor w/ 5 levels "\\N","EXCELLENT",..: 4 4 2 2 2 2 2 4 2 4 ...
$buyer_returned: Factor w/ 2 levels "\001","\\0": 2 2 2 1 2 2 2 2 2 2 ... > str(m) List of 4$ apriori: 'table' int [1:2(1d)] 2865 47135
..- attr(*, "dimnames")=List of 1
.. ..$Y: chr [1:2] "\001" "\\0"$ tables :List of 2
..$owns_home : num [1:2, 1:2] 0.358 0.268 0.479 0.443 .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ Y        : chr [1:2] "\001" "\\0"
.. .. ..$owns_home: NULL ..$ credit_type: table [1:2, 1:5] 0.1888 0.086 0.3218 0.4358 0.0932 ...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$Y : chr [1:2] "\001" "\\0" .. .. ..$ credit_type: chr [1:5] "\\N" "EXCELLENT" "FAIR" "GOOD" ...
$levels : chr [1:2] "\001" "\\0"$ call   : language naiveBayes.default(x = X, y = Y, laplace = laplace)
- attr(*, "class")= chr "naiveBayes"

I am trying to get the predicted values for each lead_id.