Predicting income is a classic regression problem. Your input data X includes all relevant information about individuals in the data set that can be used to predict income, such as years of education, years of work experience, job title, or zip code. These attributes are called features, which can be numerical (e.g. years of work experience) or categorical (e.g. job title or field of study).