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All trained machine learning models have error. We have two broad categories of errors: 1) reducible and 2) irreducible. Business analysts attempt to reduce the reducible error component by (among others) adding new data, modifying hyper-parameters or using different algorithms.

Types of error

Irreducible error comes from the fact that all phenomenon have a random component that is not predictable using any algorithm.