Multicollinearity

Definition

Multicollinearity is an Model Development issue that needs attention when developing prediction of classification risk models. It concerns the phenomenon where there is significant correlation between explanatory variables (or characteristics). The estimated coefficient estimates (e.g. in linear or logistic regression) may change significantly in response to small changes in the model or the data.