adult.data: Adult Dataset

In predfairness: Discrimination Mitigation for Machine Learning Models

Description

Sample extracted from the 1994 USA census. Each observation is related to an individual.

Format

Data frame with 32,561 rows and 15 columns.

• income: factor, >50K / <=50K. Income of each person.

• age: integer, age of each person.

• workclass factor, category of work. Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked.

• fnlwgt: numeric

• education: factor. Bachelors, Some-college, 11th, HS-grad, Prof-school, Assoc-acdm, Assoc-voc, 9th, 7th-8th, 12th, Masters, 1st-4th, 10th, Doctorate, 5th-6th, Preschool.

• education_num: numeric. Variable education converted to numeric.

• marital-status: factor of marital status. Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, Married-AF-spouse.

• occupation: factor. Tech-support, Craft-repair, Other-service, Sales, Exec-managerial, Prof-specialty, Handlers-cleaners, Machine-op-inspct, Adm-clerical, Farming-fishing, Transport-moving, Priv-house-serv, Protective-serv, Armed-Forces.

• relationship:: factor. Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried.

• race: factor. White, Asian-Pac-Islander, Amer-Indian-Eskimo, Other, Black.

• capital_gain: numeric.

• capital_loss. numeric.

• hours-per-week: numeric. Worked hours per week.

• native-country:: factor. Country of origin.

Value

Returns a data frame with 32,561 rows and 15 columns.

Source

Dataset extracted from: UCL Machine Learning Repository

References

Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

Examples

 data('adult.data')

predfairness documentation built on July 28, 2021, 5:08 p.m.