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Provide a parameter in order to decide if None/np.nan should be considered missing value or normal value #34

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smarie opened this issue Sep 22, 2022 · 1 comment

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@smarie
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smarie commented Sep 22, 2022

Two different concepts:

  • A missing value should not be used in calculations of entropy or conditional entropies, and should be only used as "last resort" in the feature selection model (Series.mode have a flag to ignore nans)
  • a "none" level, if considered an acceptable value, should be used in entropy calculations and in the calculation of mode in the feature selection model.
@smarie
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smarie commented Sep 22, 2022

Maybe we just need two parameters: "ignore_missing_values=True" and "missing_value=np.nan". The second can be changed for example to "N/A"

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