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due to Statistics.std behaviour: corrected=true by default, which divides the sum of errors by N-1 instead of N, and N-1 is 0 for singletons.
It's an edge case, but could arise in feature engineering pipelines where the size of available data varies. I think for the purpose of feature engineering, a singleton vector should be standardized to [0] rather than [NaN].
The text was updated successfully, but these errors were encountered:
Currently
due to
Statistics.std
behaviour:corrected=true
by default, which divides the sum of errors by N-1 instead of N, and N-1 is 0 for singletons.It's an edge case, but could arise in feature engineering pipelines where the size of available data varies. I think for the purpose of feature engineering, a singleton vector should be standardized to
[0]
rather than[NaN]
.The text was updated successfully, but these errors were encountered: