Generally speaking, we all know it's to save spaces with incremental learning.
According to the ques in stackoverflow , it also said that.
But what's the disadvantages?
What I know from my experiments is two points below:
Train with subsets of data but shouldn't be too small. I prepared very small datasets and the predict result is very worse.
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?