Datasets:

mstz
/

adult

configs:
  - config_name: income
    data_files:
      - path: income/train.csv
        split: train
    default: true
  - config_name: income-no race
    data_files:
      - path: income-no race/train.csv
        split: train
    default: false
  - config_name: race
    data_files:
      - path: race/train.csv
        split: train
    default: false
language: en
license: cc
pretty_name: Adult
size_categories: 10k<n<100k
tags:
  - tabular_classification
  - binary_classification
  - multiclass_classification
task_categories:
  - tabular-classification

Adult

The Adult dataset from the UCI ML repository. Census dataset including personal characteristic of a person, and their income threshold.

Configurations and tasks

Configuration	Task	Description
income	Binary classification	Classify the person's income as over or under the threshold.
income-no race	Binary classification	As `income`, but the `race` feature is removed.
race	Multiclass classification	Predict the race of the individual.

Usage

from datasets import load_dataset

dataset = load_dataset("mstz/adult", "income")["train"]

Features

Target feature changes according to the selected configuration and is always in last position in the dataset.

Feature	Type	Description
`age`	`[int64]`	Age of the person.
`capital_gain`	`[float64]`	Capital gained by the person.
`capital_loss`	`[float64]`	Capital lost by the person.
`education`	`[int8]`	Education level: the higher, the more educated the person.
`final_weight`	`[int64]`
`hours_worked_per_week`	`[int64]`	Hours worked per week.
`marital_status`	`[string]`	Marital status of the person.
`native_country`	`[string]`	Native country of the person.
`occupation`	`[string]`	Job of the person.
`race`	`[string]`	Race of the person.
`relationship`	`[string]`
`is_male`	`[bool]`	Man/Woman.
`workclass`	`[string]`	Type of job of the person.
over_threshold	`int8`	`1` for income `>= 50k$`, `0` otherwise.