Performance: as.factor > factor when input is integer A factor variable is the next of kin of an integer variable. ... This means that converting an integer to a factor is easier than converting a numeric / character to a factor. as.factor just takes care of this.
Why use as.factor () instead of just factor () - Stack Overflow
I'm currently looking into how we should remove expired certificates from Azure Multi-Factor Auth Client, and properly cleanup the old certificates with Microsoft Graph PowerShell cmdlets.
The levels of a factor are stored as character data type anyway (attributes(f)), so I don't think there is anything wrong with as.numeric(paste(f)). Perhaps it would be better to think why (in the specific context) you are getting a factor in the first place, and try to stop that. E.g., is the dec argument in read.table set correctly?
r - How to convert a factor to integer\numeric without loss of ...
The complete conversion of every character variable to factor usually happens when reading in data, e.g., with stringsAsFactors = TRUE, but this is useful when say, you've read data in with read_excel() from the readxl package and want to train a random forest model that doesn't accept character variables.
You should do the data processing step outside of the model formula/fitting. When creating the factor from b you can specify the ordering of the levels using factor(b, levels = c(3,1,2,4,5)). Do this in a data processing step outside the lm() call though. My answer below uses the relevel() function so you can create a factor and then shift the reference level around to suit as you need to.