Usage examples

The links below reference IPython notebooks where you can see how to apply EmpiricalRiskMinimization.jl for various (increasingly complex) use cases.

Examples of models on simple data

These examples link to notebooks that demonstrate how to use ERM.jl for various common machine learning models. They use randomly generated data; the focus is on optional and extended features that ERM makes available to users.

• Linear regression

• Robust regression

• Logistic regression

• Support vector machine

Examples of models on real datasets

These examples link to notebooks demonstrating ho wto use ERM.jl on real data. Many of these examples come from the EE104 lectures.

• Housing prices

• Diabetes progression