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Running more or less vanilla github example code -- besides definition of window lengths --, for batch/streaming.
Batch runs through, however streaming throws an error when scoring test values, regarding sklearn and numpy functions.
Stack-Overflowing the error reveals a known and identifiable cause, i think the problem is rooted in the way the data array is given to sklearn/numpy.
Hi @sebapehl ,
The issue being the size of the scoring window. Window Density model tracks data over window and expects the scoring window size to be similar as the training window size (reference). In your notebook, you have set the window_size = 7 and therefore, your test_size needs to be 7 as well. I just gave it a try in the colab notebook and it worked fine.
Kindly let me know if you come up with any further issues!
Running more or less vanilla github example code -- besides definition of window lengths --, for batch/streaming.
Batch runs through, however streaming throws an error when scoring test values, regarding sklearn and numpy functions.
Stack-Overflowing the error reveals a known and identifiable cause, i think the problem is rooted in the way the data array is given to sklearn/numpy.
Reproducible example at google colab.
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