StackExchange newcomer here...I am looking for some advice on feature selection packages in R. Specifically, I am in search of functions that can identify the best features, out of 500+ features, within a data set that is 500 or less observations. Most of what I have tried to date (i.e. Regsubsets, Genetic Algorithm, etc.) does not provide results in less than 24 hours. I need the function(s) to be efficient enough that it can be run on a desktop and produce results in a timely manner. Lastly, I need the function to find the best combination of features from a linear regression perspective (similar to Regsubsets).
Ideally, the "winner" would be able to do all that I have mentioned above on a standard desktop/laptop in these time frames:
- 50 or less features < 1 minute
- 250 features < 3 minutes
- 1000 features < 10 minutes
Fyi...I am mostly concerned with data sets that have linear relationships between features. By "best" I am referring to highest Adjusted R2 and lowest RMSE.