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Warning when using sparse categorical values #6383
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mjalse
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Warning when using sparse categorical values with LightGBM
Warning when using sparse categorical values
Mar 26, 2024
I guess that was the reason.
So if we use a categorical feature with many different sparse values, a large histogram would be generated and it can be memory consuming. Pardon me if I am wrong. |
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I have question about a warning message when training a LightGBM model with
lgbm.train
. I get the following warning:The reason is that I have a column, specified as categorical, that contains the following integers:
In the documentation it says:
My values are not particularly large. The "consider using consecutive integers starting from zero" seems to be a suggestion. What happens if they do not? How does the sparseness affect the performance of LightGBM? Another categorical column of my dataset has the three values
and this column does not cause the same warning.
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