R XGBoost - xgb.save or xgb.load loss of data

Question

After training an XGBoost model in R, I am presented with a model object called xgb which is a list of 7.

When I save the model using xgb.save and then reload using xgb.load, I am presented with what seems to be a 'smaller' model object which is a list of 2.

Obviously I can't share the code as you would need the training data which is massive, so all I can really show is a picture of the variable editor.

Below is model object xgb which is the original model after training, vs. the model object test1 which is the same model but saved and reloaded:

Why does this happen and am I losing valuable information upon saving/loading my models?

Any help is appreciated.

Samuel Reuther Samuel Reuther · Accepted Answer · 2019-01-21T07:27:03

Maybe late, but I was having the same problem and found a solution.

Saving the xgb-model as "rds" doesn't loose any information and the reloaded model xgb_ does generate the same forecast values as the original xgb when I tested it. Hope that helps!

saveRDS(xgb, "model.rds")
xgb_ <- readRDS("model.rds")
all.equal(xgb, xgb_)

R XGBoost - xgb.save or xgb.load loss of data

2 Answers