DEVELOPMENT... { "data_id": "337", "name": "SPECTF", "exact_name": "SPECTF", "version": 1, "version_label": null, "description": "**Author**: Krzysztof J. Cios\",\"Lukasz A. \n**Source**: [original](https:\/\/archive.ics.uci.edu\/ml\/datasets\/SPECTF+Heart) - \n**Please cite**: \n\nSPECTF heart data\n\nThis is a merged version of the separate train and test set which are usually distributed. On OpenML this train-test split can be found as one of the possible tasks. \n\nNOTE: See the SPECT heart data for binary data for the same classification task.\n\nSources: \n-- Original owners: Krzysztof J. Cios, Lukasz A. Kurgan University of Colorado at Denver, Denver, CO 80217, U.S.A. Krys.Cios@cudenver.edu Lucy S. Goodenday Medical College of Ohio, OH, U.S.A. \n-- Donors: Lukasz A.Kurgan, Krzysztof J. Cios \n-- Date: 10\/01\/01 \n\nRelevant Information: The dataset describes diagnosing of cardiac Single Proton Emission Computed Tomography (SPECT) images. Each of the patients is classified into two categories: normal and abnormal. The database of 267 SPECT image sets (patients) was processed to extract features that summarize the original SPECT images. As a result, 44 continuous feature pattern was created for each patient. The CLIP3 algorithm was used to generate classification rules from these patterns. The CLIP3 algorithm generated rules that were 77.0% accurate (as compared with cardiologists' diagnoses).", "format": "ARFF", "uploader": "Felicia West", "uploader_id": 2, "visibility": "public", "creator": "Krzysztof J. 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