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Booster.predict()
I have a question about the behavior of Booster.predict(), when the input data has incorrect number of columns.
For example, a model mdl is trained on X_train which has 10 features, and both operations below raised no exception:
mdl
X_train
y_pred_1 = mdl.predict(X_with_only_5_columns) # success y_pred_2 = mdl.predict(X_with_20_columns) # success
Could someone explain the behavior in each of the two cases above?
The text was updated successfully, but these errors were encountered:
@jsh9
Unfortunately, this is a bug and duplicate of #812. So, closing this issue as duplicate.
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I have a question about the behavior of
Booster.predict()
, when the input data has incorrect number of columns.For example, a model
mdl
is trained onX_train
which has 10 features, and both operations below raised no exception:Could someone explain the behavior in each of the two cases above?
The text was updated successfully, but these errors were encountered: