qu bit (Mar 18 2021 at 04:56): qu bit (Mar 18 2021 at 04:56):qu bit
Apply the filter & percentile method to
remove outliers from the IQR as:
begin
first_perc = percentile(DF.B, 25)
last_perc = percentile(DF.B,75)
IQR_value = iqr(DF.B)
DF_NO = filter(x -> x.B .> first_perc - 1.5*IQR_value &&
x.B .< last_perc + 1.5*IQR_value , DF)
end
You can then check the :std using the describe() method
to see what improvement might have been made from the
process (es).
Fredrik Bagge Carlson (Mar 18 2021 at 05:30):Have a look at
https://github.com/jbytecode/LinRegOutliers
qu bit (Mar 24 2021 at 21:40):Fredrik Bagge Carlson
Thanks for sharing.
I wanted to extend the question a little
and was curious if the detectOutliers()
method could be used to remove rows
by index from a dataFrame where the
outlier's were detected (i.e. via Cook's
Distance).
Best,
@Andrey Oskin
qu bit (Mar 25 2021 at 00:10):Fredrik Bagge Carlson
Could you provide an example how this could
be applied to the question I posted?
Thank you,
Last updated: Oct 02 2023 at 04:34 UTC