Dear Team, reading through the link you added at the section (https://learn.365datascience.com/courses/machine-learning-in-python/a-note-on-multicollinearity/) and doing some further reading, i understand that deciding whether a variable is a control variable or not can be sometimes pretty subjective. like in the given practice data 'Registration' could be a control or a main variable. but there is a different rule when you decide that the given feature is a control variable as you can neglect multicollinearity (if it was not binary). as i understand for the algorithm it doesnt really matter, the math is the same and it is mostly a theoretical distinction. am i right in that simplified view point and/or what is the fine line between being control or not. regards, peter

Hey Peter, Thank you for this follow-up question! Allow me to redirect you to this thread where a similar question regarding control variables has been answered in great detail. Kind regard, 365 Hristina

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Peter Simsa

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16 Feb 2022

Posted on:

15 Feb 2022

control variables and multicollinearity in regression

in Machine Learning in Python / A note on multicollinearity

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Hristina Hristova

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Posted on:

16 Feb 2022

control variables and multicollinearity in regression

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