Have looked at data on oob but would like to use it as a metric in a grid search on a Random Forest classifier (multiclass) but doesn't seem to be a recognised scorer for the scoring parameter . I do have OoB set to True in the classifier . Currently using scoring ='accuracy' but would like to change to oob score . Ideas or comments welcome
Sorry - I know this is on old thread but try calling "model.oob_score_" after running your model fit. It should give the OOB accuracy
Check out the make_scorer function in sklearn: http://scikit-learn.org/stable/modules/generated/sklearn.metrics.make_scorer.html
You may need to code the OoB component yourself, I haven't ever used that metric for scoring before with Sklearn, so I don't know for sure.
Also, consider using random search rather than grid search, it is more practical when dealing with a large hyper parameter space, since it does not need to search the entire dimension of a parameters that have no impact.