NOTE: my limited experience is with Random Forest using R.
Are there any special considerations when using Random Forest (in R) that I should be aware of with respect to the impact of correlated variables or variables derived from other variables in the dataset?
For example if I am trying to predict who might leave our company to go work for another company I might include variables such as the ones listed below. Do I need to be cautious with commingling these variables especially since, for example with Age variable, all are based on the same variable: birthdate? Or rollup fields: Age rolls up to "Age Cohorts" and "Age Cohorts" rolls up to "Age Career Cohort"?
From what I understand Random Forest has feature selection but not sure what this says about correlated fields or fields derived from other fields like the above rollup example.
BIRTHDATE BASED VARIABLES (all categorical variables except 'Birth year' and Age)
- Age Cohorts (i.e. 20-30, 30-40 yrs old, etc)
- Age Career Cohort (similar to above but wider bin i.e ("Early (Age <35)", "Mid (Age 35-49", etc)
- Birth year (probably not in R since more than 32 categories)
- Generation (i.e. Boomers, Generation X, Y, etc)
Hire Date BASED VARIABLES
- Years of Service
- Years of service chorts
Or even, for example age and service are correlated (r~.57).?