Monotonicity is when a line always slopes upwards or always slopes downwards. It is important that models behave according to business rules. So, sometimes monotonic behavior is highly desirable. For example:
for credit scoring, an applicant with a higher income should always have a lower probability of a loan going bad, everything else being equal
for pricing, a price should always be higher when the quantity of product is higher, or when the quality of product is higher
But sometimes, due to chance, the historical data causes a feature effects line that isn't monotonic when it should be.
In the Lending Club example above, you can see occasional upward blips in the feature effects and an upward slope at the end. This is not desirable behavior.
So, DataRobot gives you the choice to set constraints on the slope of feature effects. When you first set up a project, before you click the start button, use advanced settings to set which features must slope upwards versus the target, and which must slope downwards.
In the screenshot above, you can see the feature effects on a model where I have applied these constraints. No more blips. No more upward slope at the end.