adult#
The data set contains features for binary prediction of the income of an adult (the adult dataset).
The data has 48842 records with 14 features and one binary target column, referring to whether the person’s income is greater than 50K.
This is a copy of UCI ML Adult dataset. https://archive.ics.uci.edu/ml/datasets/adult
- References:
Ron Kohavi, “Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid”, Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, 1996
The typical ML task in this dataset is to build a model that determines whether a person makes over 50K a year.
- Dataset Shape:
Dataset Shape# Property
Value
Samples Total
48842
Dimensionality
14
Features
real, string
Targets
2
Samples per class
‘>50K’ - 23.93%, ‘<=50K’ - 76.07%
- Description:
Dataset Description# Column name
Column Role
Description
Age
Feature
The age of the person.
workclass
Feature
[Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked]
fnlwgt
Feature
Final weight.
education
Feature
- [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
Feature
Number of years of education
marital-status
Feature
- [Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent,
Married-AF-spouse]
occupation
Feature
- [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
Feature
[Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried]
race
Feature
[White, Asian-Pac-Islander, Amer-Indian-Eskimo, Other, Black]
sex
Feature
[Male, Female]
capital-gain
Feature
The capital gain of the person
capital-loss
Feature
The capital loss of the person
hours-per-week
Feature
The number of hours worked per week
native-country
Feature
- [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]
target
Target
The target variable, whether the person makes over 50K a year.
Functions
|
Load and returns the Adult dataset (classification). |
|
Load and return a fitted classification model. |