VIF or 1/tolerance is a good measure of measuring multicollinearity in models. VIF is the percentage of the variance of a predictor which remains unaffected by other predictors. So higher the VIF value, greater is the multicollinearity amongst the predictors.
A rule of thumb for interpreting the variance inflation factor :
* 1 = not correlated.
* Between 1 and 5 = moderately correlated.
* Greater than 5 = highly correlated.
