I want to use subgroup discovery to find some interesting patterns in a small subset of my dataset. The dataset contains about 100.000 records, the subset I want to look at only 100 records. Does it make sense to use subgroup discovery then or do I have not enough records for that. However, if this should be possible, which quality function and which algorithm (e.g. BeamSearch) would you recommend for this task and why?
Data Science Stack Exchange is a question and answer site for Data science professionals, Machine Learning specialists, and those interested in learning more about the field. It only takes a minute to sign up.
Sign up to join this community
Anybody can ask a question
Anybody can answer
The best answers are voted up and rise to the top
