I know that wikipedia references are sometimes frowned upon here, but this one has me puzzled: Wikipedia - Multicollinearity
I know what
multicollinearity is, and today I tried figuring out how/if it would affect performance of machine learning models.
At the beginning of the article, it says
Multicollinearity does not reduce the predictive power or reliability of the model as a whole
...but, as I read on it says that
A principal danger of such data redundancy is that of overfitting in regression analysis models
and I know that overfitting increases variance greatly, and can degrade performance severely.
Are either of these or both of these statements wrong?