Predict Likert Type Classification Data in R

General
1

Currently, I am working on a dataset which classification class is a Likert type. Which is

1 = " Very Easy"
2 = " Easy"
3 = " Neutral "
4= " Hard "
5 = "Very Hard "
I create a multiple linear type regression model. Now I am trying to predict a class using my model. But the output is 3.45. So this result belongs to which class? 3 or 4. though it's a Likert type data it should be either 3 or 4. How can I convert this decimal value to Likert type data in R?

Here Is my code in R

dataset <- read.csv('survey.csv')
library(caTools)  
set.seed(123)
split = sample.split(dataset$difficulty, SplitRatio = .8)
training_set = subset(dataset, split == TRUE)
test_set = subset(dataset, split == FALSE)
predict = data.frame(class = 3, nb.repeat = 1 , attendance = 3,
                 instr = 1, Q9 = 1,  Q16 = 4, Q17 =  5,
                 Q18 = 2,   Q26 =3,  Q22 = 3,Q5 = 5  )
demo_pred = predict(regressor, newdata = predict)
view(demo_pred)
1 Like
2

There's no clear demarcation between continuous and categorical dependent variables. A rule of thumb is that a dependent variable with more than 9 categories may be treated as continuous if the OLS regression is tractable.