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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

mushroom

Unsupported data preview format `arff`

mushroom

Loading data...

Schema

nametypeformat
cap-shapestringdefault
cap-surfacestringdefault
cap-colorstringdefault
bruises%3Fstringdefault
odorstringdefault
gill-attachmentstringdefault
gill-spacingstringdefault
gill-sizestringdefault
gill-colorstringdefault
stalk-shapestringdefault
stalk-rootstringdefault
stalk-surface-above-ringstringdefault
stalk-surface-below-ringstringdefault
stalk-color-above-ringstringdefault
stalk-color-below-ringstringdefault
veil-typestringdefault
veil-colorstringdefault
ring-numberstringdefault
ring-typestringdefault
spore-print-colorstringdefault
populationstringdefault
habitatstringdefault
classstringdefault

Data Files

FileDescriptionSizeLast modifiedDownload
mushroom
751 kB3 months ago
mushroom
mushroom
740 kB3 months ago
mushroom
FilesSizeFormatCreatedUpdatedLicenseSource
21.49 MBarff, 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/24

Author: Jeff Schlimmer
Source: UCI - 1981
Please cite: The Audubon Society Field Guide to North American Mushrooms (1981). G. H. Lincoff (Pres.), New York: Alfred A. Knopf

Description

This dataset describes mushrooms in terms of their physical characteristics. They are classified into: poisonous or edible.

Source

(a) Origin: 
Mushroom records are drawn from The Audubon Society Field Guide to North American Mushrooms (1981). G. H. Lincoff (Pres.), New York: Alfred A. Knopf 

(b) Donor: 
Jeff Schlimmer (Jeffrey.Schlimmer '@' a.gp.cs.cmu.edu)

Dataset description

This dataset includes descriptions of hypothetical samples corresponding to 23 species of gilled mushrooms in the Agaricus and Lepiota Family. Each species is identified as definitely edible, definitely poisonous, or of unknown edibility and not recommended. This latter class was combined with the poisonous one. The Guide clearly states that there is no simple rule for determining the edibility of a mushroom; no rule like “leaflets three, let it be” for Poisonous Oak and Ivy.

Attributes Information

1. cap-shape: bell=b,conical=c,convex=x,flat=f, knobbed=k,sunken=s 
2. cap-surface: fibrous=f,grooves=g,scaly=y,smooth=s 
3. cap-color: brown=n,buff=b,cinnamon=c,gray=g,green=r, pink=p,purple=u,red=e,white=w,yellow=y 
4. bruises?: bruises=t,no=f 
5. odor: almond=a,anise=l,creosote=c,fishy=y,foul=f, musty=m,none=n,pungent=p,spicy=s 
6. gill-attachment: attached=a,descending=d,free=f,notched=n 
7. gill-spacing: close=c,crowded=w,distant=d 
8. gill-size: broad=b,narrow=n 
9. gill-color: black=k,brown=n,buff=b,chocolate=h,gray=g, green=r,orange=o,pink=p,purple=u,red=e, white=w,yellow=y 
10. stalk-shape: enlarging=e,tapering=t 
11. stalk-root: bulbous=b,club=c,cup=u,equal=e, rhizomorphs=z,rooted=r,missing=? 
12. stalk-surface-above-ring: fibrous=f,scaly=y,silky=k,smooth=s 
13. stalk-surface-below-ring: fibrous=f,scaly=y,silky=k,smooth=s 
14. stalk-color-above-ring: brown=n,buff=b,cinnamon=c,gray=g,orange=o, pink=p,red=e,white=w,yellow=y 
15. stalk-color-below-ring: brown=n,buff=b,cinnamon=c,gray=g,orange=o, pink=p,red=e,white=w,yellow=y 
16. veil-type: partial=p,universal=u 
17. veil-color: brown=n,orange=o,white=w,yellow=y 
18. ring-number: none=n,one=o,two=t 
19. ring-type: cobwebby=c,evanescent=e,flaring=f,large=l, none=n,pendant=p,sheathing=s,zone=z 
20. spore-print-color: black=k,brown=n,buff=b,chocolate=h,green=r, orange=o,purple=u,white=w,yellow=y 
21. population: abundant=a,clustered=c,numerous=n, scattered=s,several=v,solitary=y 
22. habitat: grasses=g,leaves=l,meadows=m,paths=p, urban=u,waste=w,woods=d

Relevant papers

Schlimmer,J.S. (1987). Concept Acquisition Through Representational Adjustment (Technical Report 87-19). Doctoral disseration, Department of Information and Computer Science, University of California, Irvine.

Iba,W., Wogulis,J., & Langley,P. (1988). Trading off Simplicity and Coverage in Incremental Concept Learning. In Proceedings of the 5th International Conference on Machine Learning, 73-79. Ann Arbor, Michigan: Morgan Kaufmann.

Duch W, Adamczak R, Grabczewski K (1996) Extraction of logical rules from training data using backpropagation networks, in: Proc. of the The 1st Online Workshop on Soft Computing, 19-30.Aug.1996, pp. 25-30, [Web Link]

Duch W, Adamczak R, Grabczewski K, Ishikawa M, Ueda H, Extraction of crisp logical rules using constrained backpropagation networks - comparison of two new approaches, in: Proc. of the European Symposium on Artificial Neural Networks (ESANN'97), Bruge, Belgium 16-18.4.1997.