Machine Learning Overview (page 3 of 13)

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, managing outliers, modifying hyper-parameters or using different algorithms.



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