Measuring the degradation of a machine learning model
copied from cf-staging / pydriftHow do we measure the degradation of a machine learning process?
Why does the performance of our predictive models decrease? Maybe it is
that a data source has changed (one or more variables) or maybe what
changes is the relationship of these variables with the target we want
to predict. pydrift
tries to facilitate this task to the data scientist,
performing this kind of checks and somehow measuring that degradation.