Generally speaking, we all know it's to save spaces with incremental learning.
According to the ques in stackoverflow <https://cs.stackexchange.com/questions/51260/what-are-the-advantages-of-online-learning-when-training-neural-networks> , it also said that. But what's the disadvantages? What I know from my experiments is two points below: 1. Train with subsets of data *but shouldn't be too small*. I prepared very small datasets and the predict result is very worse. 2. When training for a very long time, some elder behavors will be forgotten due to the multiple training epochs. That's all from my experience when training with *xgboost* incrementally. Or anything else?
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
