You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I left a note here: #35, but thought it might warrant its own issue (if this package is still being developed). scale_pos_weight is only for binary classification, is there an alternative for dealing with class imbalance in multiclass classifications? I don't know mlr well, but perhaps xgboost.DMatrix(..., weight = *weight array for individual weights*), or passing .weights to trainLearner.classif.xgboost, or perhaps there is a better alternative?
The text was updated successfully, but these errors were encountered:
I left a note here: #35, but thought it might warrant its own issue (if this package is still being developed).
scale_pos_weight
is only for binary classification, is there an alternative for dealing with class imbalance in multiclass classifications? I don't knowmlr
well, but perhapsxgboost.DMatrix(..., weight = *weight array for individual weights*)
, or passing.weights
totrainLearner.classif.xgboost
, or perhaps there is a better alternative?The text was updated successfully, but these errors were encountered: