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When compute values produce sparse features (e.g. BoW), X array should become sparse not matter in which format (sparse/dense) it previously was and regardless of number of features (zero, non-zero) it previously had.
Actual behavior
Sparsity of X, Y and metas is determined from the sparsity of source data, regardless of the sparsity of data coming from compute values.
Steps to reproduce the behavior
Most easily on text. Learn a classifier on one BoW data and apply it on an other data that initially has some features.
Additional info (worksheets, data, screenshots, ...)
The text was updated successfully, but these errors were encountered:
Orange version
master
Expected behavior
When compute values produce sparse features (e.g. BoW), X array should become sparse not matter in which format (sparse/dense) it previously was and regardless of number of features (zero, non-zero) it previously had.
Actual behavior
Sparsity of X, Y and metas is determined from the sparsity of source data, regardless of the sparsity of data coming from compute values.
Steps to reproduce the behavior
Most easily on text. Learn a classifier on one BoW data and apply it on an other data that initially has some features.
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Additional info (worksheets, data, screenshots, ...)
The text was updated successfully, but these errors were encountered: