Is it possible to do Normalization before Xgboost? Currently I am working on a project which uses Xgboost Regression.
Before putting data into model, I implemented Normalization, the accuracy significantly increased compared with without Normalization.
But I saw someone said that Xgboost doesn’t need Normalization .
Did someone meet the same issue as I met ?
Thanks in advance.
Xgboost is an ensemble algorithm based on decision trees, so doesn't need normalization.
You can check this on Xgboost official github: Is Normalization necessary? and this post What are the implications of scaling the features to xgboost?

I'm new in this algorithm but I'm pretty sure of what I've written