Description

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 cardilogists' diagnoses). SPECTF is a good data set for testing ML algorithms; it has 267 instances that are descibed by 45 attributes. Predicted attribute: OVERALL_DIAGNOSIS (binary) NOTE: See the SPECT heart data for binary data for the same classification task.

Related Papers

  • Carlotta Domeniconi and Bojun Yan. Nearest Neighbor Ensemble. ICPR (1). 2004. [link]
  • [link]
  • [link]

Related datasets