Adult
Donated on 4/30/1996
Predict whether annual income of an individual exceeds $50K/yr based on census data. Also known as "Census Income" dataset.
Dataset Characteristics
Multivariate
Subject Area
Social Science
Associated Tasks
Classification
Feature Type
Categorical, Integer
# Instances
48842
# Features
14
Dataset Information
Additional Information
Extraction was done by Barry Becker from the 1994 Census database. A set of reasonably clean records was extracted using the following conditions: ((AAGE>16) && (AGI>100) && (AFNLWGT>1)&& (HRSWK>0)) Prediction task is to determine whether a person's income is over $50,000 a year.
Has Missing Values?
Yes
Variables Table
| Variable Name | Role | Type | Demographic | Description | Units | Missing Values |
|---|---|---|---|---|---|---|
| age | Feature | Integer | Age | N/A | no | |
| workclass | Feature | Categorical | Income | Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked. | yes | |
| fnlwgt | Feature | Integer | no | |||
| education | Feature | Categorical | Education Level | Bachelors, Some-college, 11th, HS-grad, Prof-school, Assoc-acdm, Assoc-voc, 9th, 7th-8th, 12th, Masters, 1st-4th, 10th, Doctorate, 5th-6th, Preschool. | no | |
| education-num | Feature | Integer | Education Level | no | ||
| marital-status | Feature | Categorical | Other | Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, Married-AF-spouse. | no | |
| occupation | Feature | Categorical | Other | 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. | yes | |
| relationship | Feature | Categorical | Other | Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried. | no | |
| race | Feature | Categorical | Race | White, Asian-Pac-Islander, Amer-Indian-Eskimo, Other, Black. | no | |
| sex | Feature | Binary | Sex | Female, Male. | no |
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Additional Variable Information
Listing of attributes: >50K, <=50K. age: continuous. workclass: Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked. fnlwgt: continuous. education: 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: continuous. marital-status: Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, Married-AF-spouse. occupation: 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: Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried. race: White, Asian-Pac-Islander, Amer-Indian-Eskimo, Other, Black. sex: Female, Male. capital-gain: continuous. capital-loss: continuous. hours-per-week: continuous. native-country: United-States, Cambodia, England, Puerto-Rico, Canada, Germany, Outlying-US(Guam-USVI-etc), India, Japan, Greece, South, China, Cuba, Iran, Honduras, Philippines, Italy, Poland, Jamaica, Vietnam, Mexico, Portugal, Ireland, France, Dominican-Republic, Laos, Ecuador, Taiwan, Haiti, Columbia, Hungary, Guatemala, Nicaragua, Scotland, Thailand, Yugoslavia, El-Salvador, Trinadad&Tobago, Peru, Hong, Holand-Netherlands.
Baseline Model Performance
Dataset Files
| File | Size |
|---|---|
| adult.data | 3.8 MB |
| adult.test | 1.9 MB |
| adult.names | 5.1 KB |
| old.adult.names | 4.2 KB |
| Index | 140 Bytes |
Papers Citing this Dataset
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By Maruthi Ayyagari. 2019
Published in International Journal of Engineering Trends and Technology 67.3 (2019): 102-108.
By Amrita Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha. 2019
Published in ArXiv.
By Roozbeh Yousefzadeh, Dianne O'Leary. 2019
Published in ArXiv.
By Matthaus Kleindessner, Pranjal Awasthi, Jamie Morgenstern. 2019
Published in ArXiv.
By Pranjal Awasthi, Matthaus Kleindessner, Jamie Morgenstern. 2019
Published in ArXiv.
0 to 5 of 257
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset adult = fetch_ucirepo(id=2) # data (as pandas dataframes) X = adult.data.features y = adult.data.targets # metadata print(adult.metadata) # variable information print(adult.variables)
Becker, B. & Kohavi, R. (1996). Adult [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5XW20.
Keywords
Creators
Barry Becker
Silicon Graphics
Ronny Kohavi
ronnyk@live.com
Consultant/Stanford
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.