Indicates that two or more variables are highly correlated (for example, City and Postal Code). These variables can have a duplicate impact on the outcome. This condition is also known as multicollinearity.
Note Einstein Discovery stories are now models. We wish we could snap our fingers to update
the name everywhere, but you can expect to see the previous name in a few places until we
replace it.
Actions to Consider
Einstein Discovery recommends choosing just one variable to improve results. Consider keeping the most descriptive field (for example, City) to make insights more easily interpretable.
Detection Methodology
Einstein Discovery raises this data alert when the Cramér's V algorithm (used to test for multicollinearity) returns 0.5 or higher for two variables.