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Question: behavior of Booster.predict() with wrong number of columns #2366

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jsh9 opened this issue Aug 29, 2019 · 1 comment
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Question: behavior of Booster.predict() with wrong number of columns #2366

jsh9 opened this issue Aug 29, 2019 · 1 comment

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@jsh9
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jsh9 commented Aug 29, 2019

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:

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?

@StrikerRUS
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@jsh9

Unfortunately, this is a bug and duplicate of #812. So, closing this issue as duplicate.

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