# Does multicollinearity affect performance of a classifier?

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?

• Multicollinearity does not increase bias, but it increases variance (overfitting). – William Chiu Jan 10 '16 at 18:00
• So, are both of the above statements still true? And, is there a better way of explaining this? – Candic3 Jan 10 '16 at 18:02