2 datasets found
  1. Adult Census Income Dataset

    • kaggle.com
    Updated Jul 7, 2024
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    Priyam Choksi (2024). Adult Census Income Dataset [Dataset]. https://www.kaggle.com/datasets/priyamchoksi/adult-census-income-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 7, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Priyam Choksi
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    The following was retrieved from UCI machine learning repository.

    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.

    Description of fnlwgt (final weight)

    The weights on the Current Population Survey (CPS) files are controlled to independent estimates of the civilian noninstitutional population of the US. These are prepared monthly for us by Population Division here at the Census Bureau. We use 3 sets of controls. These are:

    A single cell estimate of the population 16+ for each state. Controls for Hispanic Origin by age and sex. Controls by Race, age and sex. We use all three sets of controls in our weighting program and "rake" through them 6 times so that by the end we come back to all the controls we used. The term estimate refers to population totals derived from CPS by creating "weighted tallies" of any specified socio-economic characteristics of the population. People with similar demographic characteristics should have similar weights. There is one important caveat to remember about this statement. That is that since the CPS sample is actually a collection of 51 state samples, each with its own probability of selection, the statement only applies within state.

  2. h

    adult-census-income

    • huggingface.co
    • opendatalab.com
    • +1more
    Updated Feb 1, 2001
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    scikit-learn (2001). adult-census-income [Dataset]. https://huggingface.co/datasets/scikit-learn/adult-census-income
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 1, 2001
    Dataset authored and provided by
    scikit-learn
    License

    https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

    Description

    Adult Census Income Dataset

    The following was retrieved from UCI machine learning repository. 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. Description of fnlwgt (final weight)… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/adult-census-income.

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Priyam Choksi (2024). Adult Census Income Dataset [Dataset]. https://www.kaggle.com/datasets/priyamchoksi/adult-census-income-dataset
Organization logo

Adult Census Income Dataset

The following was retrieved from UCI machine learning repository.

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Jul 7, 2024
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Priyam Choksi
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Description

The following was retrieved from UCI machine learning repository.

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.

Description of fnlwgt (final weight)

The weights on the Current Population Survey (CPS) files are controlled to independent estimates of the civilian noninstitutional population of the US. These are prepared monthly for us by Population Division here at the Census Bureau. We use 3 sets of controls. These are:

A single cell estimate of the population 16+ for each state. Controls for Hispanic Origin by age and sex. Controls by Race, age and sex. We use all three sets of controls in our weighting program and "rake" through them 6 times so that by the end we come back to all the controls we used. The term estimate refers to population totals derived from CPS by creating "weighted tallies" of any specified socio-economic characteristics of the population. People with similar demographic characteristics should have similar weights. There is one important caveat to remember about this statement. That is that since the CPS sample is actually a collection of 51 state samples, each with its own probability of selection, the statement only applies within state.

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