Suppose I had a simple linear regression model that had the following input or X variable:
[North] [East] [West] [South] [North, East] ... [North, East, West, South]
and I decided to numerate them like:
[North] - 0 [East] - 1 [West] - 2 [South] - 3 [North, East] - 4 ... [North, East, West, South] - 15
I had someone take a look at my model and tell me to use One Hot Encoder or One Hot Binary Encoder instead of assigning inputs like this.
My question is from a linear regression perspective what is the advantage for using OHE over my simple numerical mapping? If we can quantify an accuracy loss would it be substantial? If I had 10 model variables that I had to map like this would the loss be more substantial?
I want to know what sacrifice I'm making not using OHE