4 datasets found
  1. h

    adult-census-income

    • huggingface.co
    • opendatalab.com
    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.

  2. Adult Income Prediction Classification

    • kaggle.com
    Updated Dec 13, 2024
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    Sathyam A (2024). Adult Income Prediction Classification [Dataset]. https://www.kaggle.com/datasets/isathyam31/adult-income-prediction-classification
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 13, 2024
    Dataset provided by
    Kaggle
    Authors
    Sathyam A
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    This dataset contains information about adult income prediction. It includes the following columns:

    workclass: The type of employment (e.g., Private, Self-emp-not-inc, Federal-gov, Local-gov) fnlwgt: The number of people the census believes the entry represents education: The highest level of education achieved education-num: The numeric representation of the previous column marital-status: The marital status of the individual occupation: The occupation of the individual relationship: The relationship of the individual to their household race: The race of the individual sex: The gender of the individual capital-gain: The capital gains of the individual capital-loss: The capital losses of the individual hours-per-week: The number of hours the individual works per week country: The native country of the individual salary: The income level of the individual, which is the target variable to predict.

    The goal of this dataset is to build a model that can accurately predict the income level of an individual based on the provided features.

  3. Adult census data

    • kaggle.com
    zip
    Updated Jul 18, 2019
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    Veera Gandhi (Jyotsna Paryani) (2019). Adult census data [Dataset]. https://www.kaggle.com/jyotsnaparyani/adult-census-data
    Explore at:
    zip(444795 bytes)Available download formats
    Dataset updated
    Jul 18, 2019
    Authors
    Veera Gandhi (Jyotsna Paryani)
    Description

    Prediction task is to determine whether a person makes over 50K a year.

    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.

    Refer following link : https://archive.ics.uci.edu/ml/datasets/adult

  4. A

    ‘Income classification’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 1, 2001
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2001). ‘Income classification’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-income-classification-c37a/latest
    Explore at:
    Dataset updated
    Feb 1, 2001
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Income classification’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/lodetomasi1995/income-classification on 28 January 2022.

    --- Dataset description provided by original source is as follows ---

    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.

    --- Original source retains full ownership of the source dataset ---

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scikit-learn (2001). adult-census-income [Dataset]. https://huggingface.co/datasets/scikit-learn/adult-census-income

adult-census-income

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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