The dataset is credited to Ronny Kohavi and Barry Becker and was drawn from the 1994 United States Census Bureau data and involves using personal details such as education level to predict whether an individual will earn more or less than $50,000 per year.
The dataset provides 14 input variables that are a mixture of categorical, ordinal, and numerical data types. The complete list of variables is as follows:
- age.
- workclass.
- final_weight.
- education.
- education_years.
- marital_status.
- occupation.
- relationship.
- race.
- sex.
- capital_gain.
- capital_loss.
- hours_per_week.
- native_country.
- category