I am using RandomForest regressor on my data and I could see that the oob score was obtained to be 0.83. I am not sure how it came out to be like this. I mean my targets are high values in the range of 10^7. So if it's MSE then it should have been much higher. I don't understand what 0.83 signify here.
I am using python's RandomForestRegressor of the sklearn toolkit.
model = RandomForestRegressor(max_depth=7, n_estimators=100, oob_score=True, n_jobs=-1) model.fit(trainX, trainY )
Then I see model.oob_score_ and I get values like 0.83809026152005295