Hello, I'm figuring out some way to deal with real time regression on disk block access times. But I have multiple patterns of each block.
Ex: Some block were accessed once a month, some blocks were accessed everyday. They all have different access patterns. The question is that how to predict access pattern of each block well in real time? I tried regression.ensemble but they don't have partial_fit to fit real time. I found leanr_model.SGDRegressor and neural_network.MLPRegressor, they have partial_fit. But they only predict one result.(But result of each block shouldn't be the same cuz they have different access times) I want to predict access times of each block in real time but I don't know how to reach the same effect. Should I change algo? thx
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
