sklearn.py: expose number of CV folds and scoring metric from the config file....
Couple of changes to cross-validation within sklearn classifiers:
- expose number of CV folds and scoring metric from the config file.
- change the default number of CV folds from 3 to 5 to use more data at the expense of longer train times, is now configurable though.
- change the default number of processes used in CV from 8 to 1 to explicitly force the user to think about using more cores. This should alleviate CPU/memory request issues when using the
condor
workflow.