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When using the LiM implementation, I run it on larger datasets and everything works, as long as I don't use the option only_global=False. Whenever it is set, I get the following message:
ValueError: Unknown label type: continuous. Maybe you are trying to fit a classifier, which expects discrete classes on a regression target with continuous values.
In case of running it on with only_global=True, everything works. I checked my data and from what I can see, I correctly define the discrete_indicator to contain all discrete features.
Can you help me out here?
The text was updated successfully, but these errors were encountered:
It looks like the error was from the local search procedure, especially from the calculation from the "_loss" function or the "_bic_scoring" function. Maybe you could debug the code to see if there is anything strange.
Thanks for your interest! If any problems, please let us know.
In the case where the parameter only_global is set to True, the discrete_indicator field is used as well. It is used to compute the objective function. If you miscalculated the discrete_indicator array, the code can work but might not work well, I think.
When using the LiM implementation, I run it on larger datasets and everything works, as long as I don't use the option only_global=False. Whenever it is set, I get the following message:
ValueError: Unknown label type: continuous. Maybe you are trying to fit a classifier, which expects discrete classes on a regression target with continuous values.
In case of running it on with only_global=True, everything works. I checked my data and from what I can see, I correctly define the discrete_indicator to contain all discrete features.
Can you help me out here?
The text was updated successfully, but these errors were encountered: