I know this may be a potential duplicate question, but I found other answers didn't work in my situation.
I am using the following dataset:
> str(total_data)
'data.frame': 32260 obs. of 13 variables:
$ age : int 40 42 44 32 25 31 30 30 27 28 ...
$ workclass : Factor w/ 4 levels "Other-Unknown",..: 3 2 2 1 2 2 2 3 2 3 ...
$ education : Ord.factor w/ 7 levels "1"<"2"<"3"<"4"<..: 2 3 2 2 2 3 2 2 2 2 ...
$ marital.status : Factor w/ 5 levels "Divorced","Married",..: 2 1 2 3 3 3 3 2 2 3 ...
$ occupation : Factor w/ 6 levels "Blue-Collar",..: 5 3 6 2 1 6 6 1 1 6 ...
$ race : Factor w/ 5 levels "Amer-Indian-Eskimo",..: 1 5 1 1 5 5 5 5 5 5 ...
$ sex : Factor w/ 2 levels "Female","Male": 2 2 2 1 2 2 2 2 1 1 ...
$ hours.per.week : int 84 40 40 38 40 38 48 70 35 38 ...
$ naitive.country: Factor w/ 41 levels "?","Cambodia",..: 39 39 39 39 39 39 39 12 39 39 ...
$ classifier : chr "<=50K""<=50K"">50K""<=50K" ...
$ class_num : Factor w/ 2 levels "1","2": 1 1 2 1 1 1 1 2 1 1 ...
$ age_norm : num 0.315 0.342 0.37 0.205 0.11 ...
$ hours_norm : num 0.847 0.398 0.398 0.378 0.398 ...
I'm trying to encode the factors into binary using one_hot() but receive the following error message:
encoded_data <- one_hot(total_data, dropCols = FALSE)
ERROR MESSAGE:
Error in `[.data.frame`(dt, , cols, with = FALSE) :
unused argument (with = FALSE)
I'm not sure what the "with" argument is as I don't see it in the R documentation.
I also saw that someone suggested to use model.matrix. However, when I use that, my ordered factor gets encoded as well, which is what I'm trying to avoid.
This is what happens to my ordered factor variable:
education.L education.Q education.C education^4 education^5 education^6
-3.779645e-01 9.690821e-17 4.082483e-01 -0.5640761 4.364358e-01 -0.19738551
-1.889822e-01 -3.273268e-01 4.082483e-01 0.0805823 -5.455447e-01 0.49346377
I'm also not sure why there are sometimes letters or numbers after the attribute name. i.e. education**.L** vs education**^5**