For now only strings are accepted as the measures parameter in GridSearchCV, RandomizedSearchCV, and cross_validate. It's thus impossible to use those with measures that take specific parameters as input (e.g. #156 ), or to use custom measures.

We should then accept callables in addition to strings.

Each callable should only take the predictions parameter. In order to handle measur

The basic idea is to have a metrics package, we can start with ROC/AUC (first on GPU, then if necessary on CPU). It should mimic the SKLearn API and results:

http://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html

Requirements:

1. GPU implementation. It can use Thrust and other libraries as first step.
2. Bindings for other languages (currently CTypes but soo

Several choices:

• plumber
• Rserve
• opencpu (updated)
• jug (updated)
• something else?