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Effective Amazon Machine Learning by Alexis Perrier

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Addressing multicollinearity

The following is the definition of multicollinearity according to Wikipedia (https://en.wikipedia.org/wiki/Multicollinearity):

Multicollinearity is a phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, meaning that one can be linearly predicted from the others with a substantial degree of accuracy.

Basically, let's say you have a model with three predictors:

And one of the predictors is a linear combination (perfect multicollinearity) or is approximated by a linear combination (near multicollinearity) of two other predictors.

For instance: 

Here,  is some noise ...

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