[R] xgb.cv doesn't return feature names #5018
Labels
cross-validation
Issues related to cross validation implementation in XGBoost.
type: bug
type: r-package
Hi all,
Long fan of your efforts with the Xgboost algorithm/implementation. It is super fast and memory-friendly.
I found a problem when trying to see feature importance when using the
xgb.cv
function, namely that it doesn't return the features names when using the callbackcb.cv.predict(save_models = TRUE)
.I found this trying to plot the model importance using
xgb.plot.importance
.Does the numbers refer to the python way of counting columns (i.e., starting from 0)?
I made an MRE below:
Xgboost version: xgboost_0.90.0.2 (R package)
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