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/core/openml-datasets/
https://datahub.io/core/openml-datasets/_r/-/FRESHNESS_CHECK.md
https://datahub.io/core/openml-datasets/_r/-/README.md
https://datahub.io/core/openml-datasets/_r/-/UPDATE_SCRIPT_MAINTENANCE_REPORT.md
https://datahub.io/core/openml-datasets/_r/-/data/Bioresponse/Bioresponse.arff
https://datahub.io/core/openml-datasets/_r/-/data/Bioresponse/Bioresponse.csv
https://datahub.io/core/openml-datasets/_r/-/data/Bioresponse/README.md
https://datahub.io/core/openml-datasets/_r/-/data/Bioresponse/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/Click_prediction_small/Click_prediction_small.arff
https://datahub.io/core/openml-datasets/_r/-/data/Click_prediction_small/Click_prediction_small.csv
https://datahub.io/core/openml-datasets/_r/-/data/Click_prediction_small/README.md
https://datahub.io/core/openml-datasets/_r/-/data/Click_prediction_small/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/IMDB.drama/IMDB.drama.arff
https://datahub.io/core/openml-datasets/_r/-/data/IMDB.drama/IMDB.drama.csv
https://datahub.io/core/openml-datasets/_r/-/data/IMDB.drama/README.md
https://datahub.io/core/openml-datasets/_r/-/data/IMDB.drama/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/MagicTelescope/MagicTelescope.arff
https://datahub.io/core/openml-datasets/_r/-/data/MagicTelescope/MagicTelescope.csv
https://datahub.io/core/openml-datasets/_r/-/data/MagicTelescope/README.md
https://datahub.io/core/openml-datasets/_r/-/data/MagicTelescope/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/Satellite/README.md
https://datahub.io/core/openml-datasets/_r/-/data/Satellite/Satellite.arff
https://datahub.io/core/openml-datasets/_r/-/data/Satellite/Satellite.csv
https://datahub.io/core/openml-datasets/_r/-/data/Satellite/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/SpeedDating/README.md
https://datahub.io/core/openml-datasets/_r/-/data/SpeedDating/SpeedDating.arff
https://datahub.io/core/openml-datasets/_r/-/data/SpeedDating/SpeedDating.csv
https://datahub.io/core/openml-datasets/_r/-/data/SpeedDating/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/abalone/README.md
https://datahub.io/core/openml-datasets/_r/-/data/abalone/abalone.arff
https://datahub.io/core/openml-datasets/_r/-/data/abalone/abalone.csv
https://datahub.io/core/openml-datasets/_r/-/data/abalone/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/adult/README.md
https://datahub.io/core/openml-datasets/_r/-/data/adult/adult.arff
https://datahub.io/core/openml-datasets/_r/-/data/adult/adult.csv
https://datahub.io/core/openml-datasets/_r/-/data/adult/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/airlines/README.md
https://datahub.io/core/openml-datasets/_r/-/data/airlines/airlines.arff
https://datahub.io/core/openml-datasets/_r/-/data/airlines/airlines.csv
https://datahub.io/core/openml-datasets/_r/-/data/airlines/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/amazon-commerce-reviews/README.md
https://datahub.io/core/openml-datasets/_r/-/data/amazon-commerce-reviews/amazon-commerce-reviews.arff
https://datahub.io/core/openml-datasets/_r/-/data/amazon-commerce-reviews/amazon-commerce-reviews.csv
https://datahub.io/core/openml-datasets/_r/-/data/amazon-commerce-reviews/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/anneal/README.md
https://datahub.io/core/openml-datasets/_r/-/data/anneal/anneal.arff
https://datahub.io/core/openml-datasets/_r/-/data/anneal/anneal.csv
https://datahub.io/core/openml-datasets/_r/-/data/anneal/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/arrhythmia/README.md
https://datahub.io/core/openml-datasets/_r/-/data/arrhythmia/arrhythmia.arff
https://datahub.io/core/openml-datasets/_r/-/data/arrhythmia/arrhythmia.csv
https://datahub.io/core/openml-datasets/_r/-/data/arrhythmia/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/autoUniv-au6-1000/README.md
https://datahub.io/core/openml-datasets/_r/-/data/autoUniv-au6-1000/autoUniv-au6-1000.arff
https://datahub.io/core/openml-datasets/_r/-/data/autoUniv-au6-1000/autoUniv-au6-1000.csv
https://datahub.io/core/openml-datasets/_r/-/data/autoUniv-au6-1000/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/autos/README.md
https://datahub.io/core/openml-datasets/_r/-/data/autos/autos.arff
https://datahub.io/core/openml-datasets/_r/-/data/autos/autos.csv
https://datahub.io/core/openml-datasets/_r/-/data/autos/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/bank-marketing/README.md
https://datahub.io/core/openml-datasets/_r/-/data/bank-marketing/bank-marketing.arff
https://datahub.io/core/openml-datasets/_r/-/data/bank-marketing/bank-marketing.csv
https://datahub.io/core/openml-datasets/_r/-/data/bank-marketing/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/banknote-authentication/README.md
https://datahub.io/core/openml-datasets/_r/-/data/banknote-authentication/banknote-authentication.arff
https://datahub.io/core/openml-datasets/_r/-/data/banknote-authentication/banknote-authentication.csv
https://datahub.io/core/openml-datasets/_r/-/data/banknote-authentication/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/blood-transfusion-service-center/README.md
https://datahub.io/core/openml-datasets/_r/-/data/blood-transfusion-service-center/blood-transfusion-service-center.arff
https://datahub.io/core/openml-datasets/_r/-/data/blood-transfusion-service-center/blood-transfusion-service-center.csv
https://datahub.io/core/openml-datasets/_r/-/data/blood-transfusion-service-center/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/breast-cancer/README.md
https://datahub.io/core/openml-datasets/_r/-/data/breast-cancer/breast-cancer.arff
https://datahub.io/core/openml-datasets/_r/-/data/breast-cancer/breast-cancer.csv
https://datahub.io/core/openml-datasets/_r/-/data/breast-cancer/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/breast-w/README.md
https://datahub.io/core/openml-datasets/_r/-/data/breast-w/breast-w.arff
https://datahub.io/core/openml-datasets/_r/-/data/breast-w/breast-w.csv
https://datahub.io/core/openml-datasets/_r/-/data/breast-w/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/cardiotocography/README.md
https://datahub.io/core/openml-datasets/_r/-/data/cardiotocography/cardiotocography.arff
https://datahub.io/core/openml-datasets/_r/-/data/cardiotocography/cardiotocography.csv
https://datahub.io/core/openml-datasets/_r/-/data/cardiotocography/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/climate-model-simulation-crashes/README.md
https://datahub.io/core/openml-datasets/_r/-/data/climate-model-simulation-crashes/climate-model-simulation-crashes.arff
https://datahub.io/core/openml-datasets/_r/-/data/climate-model-simulation-crashes/climate-model-simulation-crashes.csv
https://datahub.io/core/openml-datasets/_r/-/data/climate-model-simulation-crashes/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/cmc/README.md
https://datahub.io/core/openml-datasets/_r/-/data/cmc/cmc.arff
https://datahub.io/core/openml-datasets/_r/-/data/cmc/cmc.csv
https://datahub.io/core/openml-datasets/_r/-/data/cmc/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/credit-approval/README.md
https://datahub.io/core/openml-datasets/_r/-/data/credit-approval/credit-approval.arff
https://datahub.io/core/openml-datasets/_r/-/data/credit-approval/credit-approval.csv
https://datahub.io/core/openml-datasets/_r/-/data/credit-approval/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/credit-g/README.md
https://datahub.io/core/openml-datasets/_r/-/data/credit-g/credit-g.arff
https://datahub.io/core/openml-datasets/_r/-/data/credit-g/credit-g.csv
https://datahub.io/core/openml-datasets/_r/-/data/credit-g/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/diabetes/README.md
https://datahub.io/core/openml-datasets/_r/-/data/diabetes/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/diabetes/diabetes.arff
https://datahub.io/core/openml-datasets/_r/-/data/diabetes/diabetes.csv
https://datahub.io/core/openml-datasets/_r/-/data/eeg-eye-state/README.md
https://datahub.io/core/openml-datasets/_r/-/data/eeg-eye-state/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/eeg-eye-state/eeg-eye-state.arff
https://datahub.io/core/openml-datasets/_r/-/data/eeg-eye-state/eeg-eye-state.csv
https://datahub.io/core/openml-datasets/_r/-/data/electricity/README.md
https://datahub.io/core/openml-datasets/_r/-/data/electricity/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/electricity/electricity.arff
https://datahub.io/core/openml-datasets/_r/-/data/electricity/electricity.csv
https://datahub.io/core/openml-datasets/_r/-/data/fbis.wc/README.md
https://datahub.io/core/openml-datasets/_r/-/data/fbis.wc/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/fbis.wc/fbis.wc.arff
https://datahub.io/core/openml-datasets/_r/-/data/fbis.wc/fbis.wc.csv
https://datahub.io/core/openml-datasets/_r/-/data/first-order-theorem-proving/README.md
https://datahub.io/core/openml-datasets/_r/-/data/first-order-theorem-proving/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/first-order-theorem-proving/first-order-theorem-proving.arff
https://datahub.io/core/openml-datasets/_r/-/data/first-order-theorem-proving/first-order-theorem-proving.csv
https://datahub.io/core/openml-datasets/_r/-/data/gas-drift/README.md
https://datahub.io/core/openml-datasets/_r/-/data/gas-drift/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/gas-drift/gas-drift.arff
https://datahub.io/core/openml-datasets/_r/-/data/gas-drift/gas-drift.csv
https://datahub.io/core/openml-datasets/_r/-/data/gina_agnostic/README.md
https://datahub.io/core/openml-datasets/_r/-/data/gina_agnostic/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/gina_agnostic/gina_agnostic.arff
https://datahub.io/core/openml-datasets/_r/-/data/gina_agnostic/gina_agnostic.csv
https://datahub.io/core/openml-datasets/_r/-/data/gina_prior2/README.md
https://datahub.io/core/openml-datasets/_r/-/data/gina_prior2/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/gina_prior2/gina_prior2.arff
https://datahub.io/core/openml-datasets/_r/-/data/gina_prior2/gina_prior2.csv
https://datahub.io/core/openml-datasets/_r/-/data/glass/README.md
https://datahub.io/core/openml-datasets/_r/-/data/glass/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/glass/glass.arff
https://datahub.io/core/openml-datasets/_r/-/data/glass/glass.csv
https://datahub.io/core/openml-datasets/_r/-/data/haberman/README.md
https://datahub.io/core/openml-datasets/_r/-/data/haberman/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/haberman/haberman.arff
https://datahub.io/core/openml-datasets/_r/-/data/haberman/haberman.csv
https://datahub.io/core/openml-datasets/_r/-/data/heart-statlog/README.md
https://datahub.io/core/openml-datasets/_r/-/data/heart-statlog/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/heart-statlog/heart-statlog.arff
https://datahub.io/core/openml-datasets/_r/-/data/heart-statlog/heart-statlog.csv
https://datahub.io/core/openml-datasets/_r/-/data/hill-valley/README.md
https://datahub.io/core/openml-datasets/_r/-/data/hill-valley/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/hill-valley/hill-valley.arff
https://datahub.io/core/openml-datasets/_r/-/data/hill-valley/hill-valley.csv
https://datahub.io/core/openml-datasets/_r/-/data/ilpd/README.md
https://datahub.io/core/openml-datasets/_r/-/data/ilpd/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/ilpd/ilpd.arff
https://datahub.io/core/openml-datasets/_r/-/data/ilpd/ilpd.csv
https://datahub.io/core/openml-datasets/_r/-/data/ionosphere/README.md
https://datahub.io/core/openml-datasets/_r/-/data/ionosphere/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/ionosphere/ionosphere.arff
https://datahub.io/core/openml-datasets/_r/-/data/ionosphere/ionosphere.csv
https://datahub.io/core/openml-datasets/_r/-/data/iris/README.md
https://datahub.io/core/openml-datasets/_r/-/data/iris/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/iris/iris.arff
https://datahub.io/core/openml-datasets/_r/-/data/iris/iris.csv
https://datahub.io/core/openml-datasets/_r/-/data/isolet/README.md
https://datahub.io/core/openml-datasets/_r/-/data/isolet/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/isolet/isolet.arff
https://datahub.io/core/openml-datasets/_r/-/data/isolet/isolet.csv
https://datahub.io/core/openml-datasets/_r/-/data/jm1/README.md
https://datahub.io/core/openml-datasets/_r/-/data/jm1/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/jm1/jm1.arff
https://datahub.io/core/openml-datasets/_r/-/data/jm1/jm1.csv
https://datahub.io/core/openml-datasets/_r/-/data/kc1/README.md
https://datahub.io/core/openml-datasets/_r/-/data/kc1/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/kc1/kc1.arff
https://datahub.io/core/openml-datasets/_r/-/data/kc1/kc1.csv
https://datahub.io/core/openml-datasets/_r/-/data/kc2/README.md
https://datahub.io/core/openml-datasets/_r/-/data/kc2/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/kc2/kc2.arff
https://datahub.io/core/openml-datasets/_r/-/data/kc2/kc2.csv
https://datahub.io/core/openml-datasets/_r/-/data/kr-vs-kp/README.md
https://datahub.io/core/openml-datasets/_r/-/data/kr-vs-kp/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/kr-vs-kp/kr-vs-kp.arff
https://datahub.io/core/openml-datasets/_r/-/data/kr-vs-kp/kr-vs-kp.csv
https://datahub.io/core/openml-datasets/_r/-/data/kropt/README.md
https://datahub.io/core/openml-datasets/_r/-/data/kropt/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/kropt/kropt.arff
https://datahub.io/core/openml-datasets/_r/-/data/kropt/kropt.csv
https://datahub.io/core/openml-datasets/_r/-/data/letter/README.md
https://datahub.io/core/openml-datasets/_r/-/data/letter/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/letter/letter.arff
https://datahub.io/core/openml-datasets/_r/-/data/letter/letter.csv
https://datahub.io/core/openml-datasets/_r/-/data/liver-disorders/README.md
https://datahub.io/core/openml-datasets/_r/-/data/liver-disorders/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/liver-disorders/liver-disorders.arff
https://datahub.io/core/openml-datasets/_r/-/data/liver-disorders/liver-disorders.csv
https://datahub.io/core/openml-datasets/_r/-/data/lung-cancer/README.md
https://datahub.io/core/openml-datasets/_r/-/data/lung-cancer/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/lung-cancer/lung-cancer.arff
https://datahub.io/core/openml-datasets/_r/-/data/lung-cancer/lung-cancer.csv
https://datahub.io/core/openml-datasets/_r/-/data/lymph/README.md
https://datahub.io/core/openml-datasets/_r/-/data/lymph/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/lymph/lymph.arff
https://datahub.io/core/openml-datasets/_r/-/data/lymph/lymph.csv
https://datahub.io/core/openml-datasets/_r/-/data/madelon/README.md
https://datahub.io/core/openml-datasets/_r/-/data/madelon/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/madelon/madelon.arff
https://datahub.io/core/openml-datasets/_r/-/data/madelon/madelon.csv
https://datahub.io/core/openml-datasets/_r/-/data/mammography/README.md
https://datahub.io/core/openml-datasets/_r/-/data/mammography/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/mammography/mammography.arff
https://datahub.io/core/openml-datasets/_r/-/data/mammography/mammography.csv
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-factors/README.md
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-factors/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-factors/mfeat-factors.arff
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-factors/mfeat-factors.csv
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-karhunen/README.md
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-karhunen/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-karhunen/mfeat-karhunen.arff
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-karhunen/mfeat-karhunen.csv
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-morphological/README.md
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-morphological/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-morphological/mfeat-morphological.arff
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-morphological/mfeat-morphological.csv
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-pixel/README.md
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-pixel/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-pixel/mfeat-pixel.arff
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-pixel/mfeat-pixel.csv
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-zernike/README.md
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-zernike/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-zernike/mfeat-zernike.arff
https://datahub.io/core/openml-datasets/_r/-/data/mfeat-zernike/mfeat-zernike.csv
https://datahub.io/core/openml-datasets/_r/-/data/mozilla4/README.md
https://datahub.io/core/openml-datasets/_r/-/data/mozilla4/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/mozilla4/mozilla4.arff
https://datahub.io/core/openml-datasets/_r/-/data/mozilla4/mozilla4.csv
https://datahub.io/core/openml-datasets/_r/-/data/mushroom/README.md
https://datahub.io/core/openml-datasets/_r/-/data/mushroom/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/mushroom/mushroom.arff
https://datahub.io/core/openml-datasets/_r/-/data/mushroom/mushroom.csv
https://datahub.io/core/openml-datasets/_r/-/data/musk/README.md
https://datahub.io/core/openml-datasets/_r/-/data/musk/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/musk/musk.arff
https://datahub.io/core/openml-datasets/_r/-/data/musk/musk.csv
https://datahub.io/core/openml-datasets/_r/-/data/nursery/README.md
https://datahub.io/core/openml-datasets/_r/-/data/nursery/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/nursery/nursery.arff
https://datahub.io/core/openml-datasets/_r/-/data/nursery/nursery.csv
https://datahub.io/core/openml-datasets/_r/-/data/oil_spill/README.md
https://datahub.io/core/openml-datasets/_r/-/data/oil_spill/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/oil_spill/oil_spill.arff
https://datahub.io/core/openml-datasets/_r/-/data/oil_spill/oil_spill.csv
https://datahub.io/core/openml-datasets/_r/-/data/one-hundred-plants-shape/README.md
https://datahub.io/core/openml-datasets/_r/-/data/one-hundred-plants-shape/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/one-hundred-plants-shape/one-hundred-plants-shape.arff
https://datahub.io/core/openml-datasets/_r/-/data/one-hundred-plants-shape/one-hundred-plants-shape.csv
https://datahub.io/core/openml-datasets/_r/-/data/one-hundred-plants-texture/README.md
https://datahub.io/core/openml-datasets/_r/-/data/one-hundred-plants-texture/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/one-hundred-plants-texture/one-hundred-plants-texture.arff
https://datahub.io/core/openml-datasets/_r/-/data/one-hundred-plants-texture/one-hundred-plants-texture.csv
https://datahub.io/core/openml-datasets/_r/-/data/optdigits/README.md
https://datahub.io/core/openml-datasets/_r/-/data/optdigits/datapackage.json
https://datahub.io/core/openml-datasets/_r/-/data/optdigits/optdigits.arff
https://datahub.io/core/openml-datasets/_r/-/data/optdigits/optdigits.csv
https://datahub.io/core/openml-datasets/_r/-/data/page-blocks/README.md
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Key Files

Start with these files — they give you everything you need to understand and access the dataset.

https://datahub.io/core/openml-datasets/_r/-/data/Bioresponse/datapackage.json
README.mddocumentation
https://datahub.io/core/openml-datasets/_r/-/README.md
Typical Usage
  1. 1. Fetch data/Bioresponse/datapackage.json to inspect schema and resources
  2. 2. Download data resources listed in data/Bioresponse/datapackage.json
  3. 3. Read README.md for full context

Data Previews

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Schema

nametypeformat
handicapped-infantsstringdefault
water-project-cost-sharingstringdefault
adoption-of-the-budget-resolutionstringdefault
physician-fee-freezestringdefault
el-salvador-aidstringdefault
religious-groups-in-schoolsstringdefault
anti-satellite-test-banstringdefault
aid-to-nicaraguan-contrasstringdefault
mx-missilestringdefault
immigrationstringdefault
synfuels-corporation-cutbackstringdefault
education-spendingstringdefault
superfund-right-to-suestringdefault
crimestringdefault
duty-free-exportsstringdefault
export-administration-act-south-africastringdefault
Classstringdefault

Data Files

FileDescriptionSizeLast modifiedDownload
vote
40.3 kB3 months ago
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vote
32.1 kB3 months ago
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FilesSizeFormatCreatedUpdatedLicenseSource
272.4 kBarff, csvabout 2 months agoOpen Data Commons Public Domain Dedication and License

The resources for this dataset can be found at https://www.openml.org/d/56

Author:
Source: Unknown -
Please cite:

  1. Title: 1984 United States Congressional Voting Records Database

  2. Source Information: (a) Source: Congressional Quarterly Almanac, 98th Congress, 2nd session 1984, Volume XL: Congressional Quarterly Inc. Washington, D.C., 1985. (b) Donor: Jeff Schlimmer (Jeffrey.Schlimmer@a.gp.cs.cmu.edu) (c) Date: 27 April 1987

  3. Past Usage

    • Publications
      1. Schlimmer, J. C. (1987). Concept acquisition through representational adjustment. Doctoral dissertation, Department of Information and Computer Science, University of California, Irvine, CA. – Results: about 90%-95% accuracy appears to be STAGGER's asymptote
      • Predicted attribute: party affiliation (2 classes)
  4. Relevant Information: This data set includes votes for each of the U.S. House of Representatives Congressmen on the 16 key votes identified by the CQA. The CQA lists nine different types of votes: voted for, paired for, and announced for (these three simplified to yea), voted against, paired against, and announced against (these three simplified to nay), voted present, voted present to avoid conflict of interest, and did not vote or otherwise make a position known (these three simplified to an unknown disposition).

  5. Number of Instances: 435 (267 democrats, 168 republicans)

  6. Number of Attributes: 16 + class name = 17 (all Boolean valued)

  7. Attribute Information:

    1. Class Name: 2 (democrat, republican)
    2. handicapped-infants: 2 (y,n)
    3. water-project-cost-sharing: 2 (y,n)
    4. adoption-of-the-budget-resolution: 2 (y,n)
    5. physician-fee-freeze: 2 (y,n)
    6. el-salvador-aid: 2 (y,n)
    7. religious-groups-in-schools: 2 (y,n)
    8. anti-satellite-test-ban: 2 (y,n)
    9. aid-to-nicaraguan-contras: 2 (y,n)
  8. mx-missile: 2 (y,n)

  9. immigration: 2 (y,n)

  10. synfuels-corporation-cutback: 2 (y,n)

  11. education-spending: 2 (y,n)

  12. superfund-right-to-sue: 2 (y,n)

  13. crime: 2 (y,n)

  14. duty-free-exports: 2 (y,n)

  15. export-administration-act-south-africa: 2 (y,n)

  16. Missing Attribute Values: Denoted by "?"

    NOTE: It is important to recognize that "?" in this database does not mean that the value of the attribute is unknown. It means simply, that the value is not "yea" or "nay" (see "Relevant Information" section above).

    Attribute: #Missing Values: 1: 0 2: 0 3: 12 4: 48 5: 11 6: 11 7: 15 8: 11 9: 14 10: 15 11: 22 12: 7 13: 21 14: 31 15: 25 16: 17 17: 28

  17. Class Distribution: (2 classes)

    1. 45.2 percent are democrat
    2. 54.8 percent are republican

Class predictiveness and predictability: Pr(C|A=V) and Pr(A=V|C) Attribute 1: (A = handicapped-infants) 0.91; 1.21 (C=democrat; V=y) 0.09; 0.10 (C=republican; V=y) 0.43; 0.38 (C=democrat; V=n) 0.57; 0.41 (C=republican; V=n) 0.75; 0.03 (C=democrat; V=?) 0.25; 0.01 (C=republican; V=?) Attribute 2: (A = water-project-cost-sharing) 0.62; 0.45 (C=democrat; V=y) 0.38; 0.23 (C=republican; V=y) 0.62; 0.45 (C=democrat; V=n) 0.38; 0.23 (C=republican; V=n) 0.58; 0.10 (C=democrat; V=?) 0.42; 0.06 (C=republican; V=?) Attribute 3: (A = adoption-of-the-budget-resolution) 0.91; 0.87 (C=democrat; V=y) 0.09; 0.07 (C=republican; V=y) 0.17; 0.11 (C=democrat; V=n) 0.83; 0.44 (C=republican; V=n) 0.64; 0.03 (C=democrat; V=?) 0.36; 0.01 (C=republican; V=?) Attribute 4: (A = physician-fee-freeze) 0.08; 0.05 (C=democrat; V=y) 0.92; 0.50 (C=republican; V=y) 0.99; 0.92 (C=democrat; V=n) 0.01; 0.01 (C=republican; V=n) 0.73; 0.03 (C=democrat; V=?) 0.27; 0.01 (C=republican; V=?) Attribute 5: (A = el-salvador-aid) 0.26; 0.21 (C=democrat; V=y) 0.74; 0.48 (C=republican; V=y) 0.96; 0.75 (C=democrat; V=n) 0.04; 0.02 (C=republican; V=n) 0.80; 0.04 (C=democrat; V=?) 0.20; 0.01 (C=republican; V=?) Attribute 6: (A = religious-groups-in-schools) 0.45; 0.46 (C=democrat; V=y) 0.55; 0.46 (C=republican; V=y) 0.89; 0.51 (C=democrat; V=n) 0.11; 0.05 (C=republican; V=n) 0.82; 0.03 (C=democrat; V=?) 0.18; 0.01 (C=republican; V=?) Attribute 7: (A = anti-satellite-test-ban) 0.84; 0.75 (C=democrat; V=y) 0.16; 0.12 (C=republican; V=y) 0.32; 0.22 (C=democrat; V=n) 0.68; 0.38 (C=republican; V=n) 0.57; 0.03 (C=democrat; V=?) 0.43; 0.02 (C=republican; V=?) Attribute 8: (A = aid-to-nicaraguan-contras) 0.90; 0.82 (C=democrat; V=y) 0.10; 0.07 (C=republican; V=y) 0.25; 0.17 (C=democrat; V=n) 0.75; 0.41 (C=republican; V=n) 0.27; 0.01 (C=democrat; V=?) 0.73; 0.03 (C=republican; V=?) Attribute 9: (A = mx-missile) 0.91; 0.70 (C=democrat; V=y) 0.09; 0.06 (C=republican; V=y) 0.29; 0.22 (C=democrat; V=n) 0.71; 0.45 (C=republican; V=n) 0.86; 0.07 (C=democrat; V=?) 0.14; 0.01 (C=republican; V=?) Attribute 10: (A = immigration) 0.57; 0.46 (C=democrat; V=y) 0.43; 0.28 (C=republican; V=y) 0.66; 0.52 (C=democrat; V=n) 0.34; 0.23 (C=republican; V=n) 0.57; 0.01 (C=democrat; V=?) 0.43; 0.01 (C=republican; V=?) Attribute 11: (A = synfuels-corporation-cutback) 0.86; 0.48 (C=democrat; V=y) 0.14; 0.06 (C=republican; V=y) 0.48; 0.47 (C=democrat; V=n) 0.52; 0.43 (C=republican; V=n) 0.57; 0.04 (C=democrat; V=?) 0.43; 0.03 (C=republican; V=?) Attribute 12: (A = education-spending) 0.21; 0.13 (C=democrat; V=y) 0.79; 0.42 (C=republican; V=y) 0.91; 0.80 (C=democrat; V=n) 0.09; 0.06 (C=republican; V=n) 0.58; 0.07 (C=democrat; V=?) 0.42; 0.04 (C=republican; V=?) Attribute 13: (A = superfund-right-to-sue) 0.35; 0.27 (C=democrat; V=y) 0.65; 0.42 (C=republican; V=y) 0.89; 0.67 (C=democrat; V=n) 0.11; 0.07 (C=republican; V=n) 0.60; 0.06 (C=democrat; V=?) 0.40; 0.03 (C=republican; V=?) Attribute 14: (A = crime) 0.36; 0.34 (C=democrat; V=y) 0.64; 0.49 (C=republican; V=y) 0.98; 0.63 (C=democrat; V=n) 0.02; 0.01 (C=republican; V=n) 0.59; 0.04 (C=democrat; V=?) 0.41; 0.02 (C=republican; V=?) Attribute 15: (A = duty-free-exports) 0.92; 0.60 (C=democrat; V=y) 0.08; 0.04 (C=republican; V=y) 0.39; 0.34 (C=democrat; V=n) 0.61; 0.44 (C=republican; V=n) 0.57; 0.06 (C=democrat; V=?) 0.43; 0.04 (C=republican; V=?) Attribute 16: (A = export-administration-act-south-africa) 0.64; 0.65 (C=democrat; V=y) 0.36; 0.30 (C=republican; V=y) 0.19; 0.04 (C=democrat; V=n) 0.81; 0.15 (C=republican; V=n) 0.79; 0.31 (C=democrat; V=?) 0.21; 0.07 (C=republican; V=?)