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vruusmann avatar vruusmann commented on August 20, 2024

My internal TODO list has quite a few open items about the pandas.Int64Dtype data type support.

The current issue can be corrected by initializing the CategoricalDomain.data_values_ attribute using the data_values constructor parameter:

cat_domain = CategoricalDomain(data_values = [[1, 2, 3]])

Alternatively, a problematic attribute may be manually simplified to a dense/unmasked numpy array:

cat_domain.data_values_ = numpy.asarray(cat_domain.data_values_.tolist())

Perhaps such simplification should be applied automatically by the CategoricalDomain.fit(X, y) method.

from sklearn2pmml.

a-rudnik avatar a-rudnik commented on August 20, 2024

Thanks for the quick response.
The suggested solution resolves the issue.

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vruusmann avatar vruusmann commented on August 20, 2024

Reopening, because the conversion should succeed without any manual intervention.

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