I have a data frame of approximately 11500 records.
Each row of the frame has a response variable,
isfastes, and a number of other predictors (size, cores, timeout, queue, and selection) and two other variables,
name and 'loggedtime'.
The data was generated by running a command on a provided input (identified by name) with various arguments (the predictors). I am trying to find out which combination of arguments typically leads to the fastest execution time (
isfastest) regardless of the input. When I run a random forest as
the results are:
0 1 class.error 0 11392 0 0 1 118 0 1
randomForest method is always predicting "no". At the very least I'd expect
cores alone to be significant, as when I look at the set of
isfastest == 1 rows, there are far more records where
cores == 64 than otherwise (as I would expect).
What could be causing
randomForest to consistently return 0?