Name: Adult Census Income With AI
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Adult Census Income With AI

Context

This data was extracted from the 1994 Census bureau database by Ronny Kohavi and Barry Becker (Data Mining and Visualization, Silicon Graphics). A set of reasonably clean records was extracted using the following conditions: ((AAGE>16) && (AGI>100) && (AFNLWGT>1) && (HRSWK>0)). The prediction task is to determine whether a person makes over $50K a year.

In order to make the job better we used artificial Intelligence to automatically modify the columns.

Content

This Dataset contains the initial Dataset columns as well as the new ones obtained by feeding the original US Census Dataset to PredicSis.ai in order to automatically :

Discretise continuous variables into relevant intervals.
Group values of categorical variables together in order to reduce the modality of the variables.

Acknowledgements

https://archive.ics.uci.edu/ml/datasets/Census+Income

https://www.kaggle.com/uciml/adult-census-income

https://predicsis.ai

Inspiration

We want to see by how much auto ML/AI improves the data scientist work quality.

Tables

Modified Census Data

@kaggle.blackbee2016_adult_census_income_with_ai.modified_census_data

1.29 MB
48,842 rows
30 columns

CREATE TABLE modified_census_data (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "key" BIGINT,
  "label" BIGINT,
  "age" BIGINT,
  "capital_gain" BIGINT,
  "capital_loss" BIGINT,
  "education" VARCHAR,
  "education_num" BIGINT,
  "fnlwgt" BIGINT,
  "hours_per_week" BIGINT,
  "marital_status" VARCHAR,
  "native_country" VARCHAR,
  "occupation" VARCHAR,
  "race" VARCHAR,
  "relationship" VARCHAR,
  "sex" VARCHAR,
  "worklabel" VARCHAR,
  "labelpage" VARCHAR,
  "labelpcapital_gain" VARCHAR,
  "labelpcapital_loss" VARCHAR,
  "labelpeducation" VARCHAR,
  "labelpeducation_num" VARCHAR,
  "labelphours_per_week" VARCHAR,
  "labelpmarital_status" VARCHAR,
  "labelpnative_country" VARCHAR,
  "labelpoccupation" VARCHAR,
  "labelprace" VARCHAR,
  "labelprelationship" VARCHAR,
  "labelpsex" VARCHAR,
  "labelpworklabel" VARCHAR
);