I'm new to machine learning and advanced statistics so please be patient with my basic question.
I am currently trying to model a data set I have with bunch of time data as independent variables (i.e. hour, day, month and year). With a continuous variable as the outcome, i.e. money.
My understanding is that you must convert categorical variables for knn to work.
Does that mean I must somehow convert my time data? The approach I found online was basically convert every level of a categorical variable to be a binary. But given the many possible levels, doesn't this create the dimensionality problem?
Is this a common problem with knn? Should I just use a different algorithm? Or should I seek to combine my time data into one continuous variable somehow?