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spectf_train.arff
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UCI/spectf_train.arff
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16.8 KB
2009-10-30 13:16:31
Description
SPECT heart data
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% 1. Title of Database: SPECTF heart data % % 2. Sources: % -- 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. % -- Donors: Lukasz A.Kurgan, Krzysztof J. Cios % -- Date: 10/01/01 % % 3. Past Usage: % 1. Kurgan, L.A., Cios, K.J., Tadeusiewicz, R., Ogiela, M. & Goodenday, L.S. % "Knowledge Discovery Approach to Automated Cardiac SPECT Diagnosis" % Artificial Intelligence in Medicine, vol. 23:2, pp 149-169, Oct 2001 % % Results: The CLIP3 machine learning algorithm achieved 77.0% accuracy. % CLIP3 references: % Cios, K.J., Wedding, D.K. & Liu, N. % CLIP3: cover learning using integer programming. % Kybernetes, 26:4-5, pp 513-536, 1997 % % Cios K. J. & Kurgan L. % Hybrid Inductive Machine Learning: An Overview of CLIP Algorithms, % In: Jain L.C., and Kacprzyk J. (Eds.) % New Learning Paradigms in Soft Computing, % Physica-Verlag (Springer), 2001 % % % 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. % % 4. Relevant 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 cardilogists' diagnoses). % % 5. Number of Instances: 267 % 6. Number of Attributes: 45 (44 continuous + 1 binary class) % 7. Attribute Information: % 1. OVERALL_DIAGNOSIS: 0,1 (class attribute, binary) % 2. F1R: continuous (count in ROI (region of interest) 1 in rest) % 3. F1S: continuous (count in ROI 1 in stress) % 4. F2R: continuous (count in ROI 2 in rest) % 5. F2S: continuous (count in ROI 2 in stress) % 6. F3R: continuous (count in ROI 3 in rest) % 7. F3S: continuous (count in ROI 3 in stress) % 8. F4R: continuous (count in ROI 4 in rest) % 9. F4S: continuous (count in ROI 4 in stress) % 10. F5R: continuous (count in ROI 5 in rest) % 11. F5S: continuous (count in ROI 5 in stress) % 12. F6R: continuous (count in ROI 6 in rest) % 13. F6S: continuous (count in ROI 6 in stress) % 14. F7R: continuous (count in ROI 7 in rest) % 15. F7S: continuous (count in ROI 7 in stress) % 16. F8R: continuous (count in ROI 8 in rest) % 17. F8S: continuous (count in ROI 8 in stress) % 18. F9R: continuous (count in ROI 9 in rest) % 19. F9S: continuous (count in ROI 9 in stress) % 20. F10R: continuous (count in ROI 10 in rest) % 21. F10S: continuous (count in ROI 10 in stress) % 22. F11R: continuous (count in ROI 11 in rest) % 23. F11S: continuous (count in ROI 11 in stress) % 24. F12R: continuous (count in ROI 12 in rest) % 25. F12S: continuous (count in ROI 12 in stress) % 26. F13R: continuous (count in ROI 13 in rest) % 27. F13S: continuous (count in ROI 13 in stress) % 28. F14R: continuous (count in ROI 14 in rest) % 29. F14S: continuous (count in ROI 14 in stress) % 30. F15R: continuous (count in ROI 15 in rest) % 31. F15S: continuous (count in ROI 15 in stress) % 32. F16R: continuous (count in ROI 16 in rest) % 33. F16S: continuous (count in ROI 16 in stress) % 34. F17R: continuous (count in ROI 17 in rest) % 35. F17S: continuous (count in ROI 17 in stress) % 36. F18R: continuous (count in ROI 18 in rest) % 37. F18S: continuous (count in ROI 18 in stress) % 38. F19R: continuous (count in ROI 19 in rest) % 39. F19S: continuous (count in ROI 19 in stress) % 40. F20R: continuous (count in ROI 20 in rest) % 41. F20S: continuous (count in ROI 20 in stress) % 42. F21R: continuous (count in ROI 21 in rest) % 43. F21S: continuous (count in ROI 21 in stress) % 44. F22R: continuous (count in ROI 22 in rest) % 45. F22S: continuous (count in ROI 22 in stress) % -- all continuous attributes have integer values from the 0 to 100 % -- dataset is divided into: % -- training data ("SPECTF.train" 80 instances) % -- testing data ("SPECTF.test" 187 instances) % 8. Missing Attribute Values: None % 9. Class Distribution: % -- entire data % Class # examples % 0 55 % 1 212 % -- training dataset % Class # examples % 0 40 % 1 40 % -- testing dataset % Class # examples % 0 15 % 1 172 % % NOTE: See the SPECT heart data for binary data for the same classification task. % % Information about the dataset % CLASSTYPE: nominal % CLASSINDEX: first % @relation spect @attribute OVERALL_DIAGNOSIS {0,1} @attribute F1R INTEGER @attribute F1S INTEGER @attribute F2R INTEGER @attribute F2S INTEGER @attribute F3R INTEGER @attribute F3S INTEGER @attribute F4R INTEGER @attribute F4S INTEGER @attribute F5R INTEGER @attribute F5S INTEGER @attribute F6R INTEGER @attribute F6S INTEGER @attribute F7R INTEGER @attribute F7S INTEGER @attribute F8R INTEGER @attribute F8S INTEGER @attribute F9R INTEGER @attribute F9S INTEGER @attribute F10R INTEGER @attribute F10S INTEGER @attribute F11R INTEGER @attribute F11S INTEGER @attribute F12R INTEGER @attribute F12S INTEGER @attribute F13R INTEGER @attribute F13S INTEGER @attribute F14R INTEGER @attribute F14S INTEGER @attribute F15R INTEGER @attribute F15S INTEGER @attribute F16R INTEGER @attribute F16S INTEGER @attribute F17R INTEGER @attribute F17S INTEGER @attribute F18R INTEGER @attribute F18S INTEGER @attribute F19R INTEGER @attribute F19S INTEGER @attribute F20R INTEGER @attribute F20S INTEGER @attribute F21R INTEGER @attribute F21S INTEGER @attribute F22R INTEGER @attribute F22S INTEGER @data 1,59,52,70,67,73,66,72,61,58,52,72,71,70,77,66,65,67,55,61,57,68,66,72,74,63,64,56,54,67,54,76,74,65,67,66,56,62,56,72,62,74,74,64,67 1,72,62,69,67,78,82,74,65,69,63,70,70,72,74,70,71,72,75,66,65,73,78,74,79,74,69,69,70,71,69,72,70,62,65,65,71,63,60,69,73,67,71,56,58 1,71,62,70,64,67,64,79,65,70,69,72,71,68,65,61,61,73,71,75,74,80,74,54,47,53,37,77,68,72,59,72,68,60,60,73,70,66,65,64,55,61,41,51,46 1,69,71,70,78,61,63,67,65,59,59,66,69,71,75,65,58,60,55,62,59,67,66,74,74,64,60,57,54,70,73,69,76,62,64,61,61,66,65,72,73,68,68,59,63 1,70,66,61,66,61,58,69,69,72,68,62,71,71,71,63,59,74,75,70,69,83,77,73,70,41,37,39,40,58,46,75,73,65,66,67,69,70,66,70,64,60,55,49,41 1,57,69,68,75,69,74,73,71,57,61,72,74,73,69,61,58,60,55,71,62,79,70,77,71,65,63,69,55,61,68,75,74,63,64,63,58,69,67,79,77,72,70,61,65 1,69,66,62,75,67,71,72,76,69,70,66,69,71,80,66,64,71,77,65,61,72,67,71,69,65,57,69,65,68,65,76,73,63,64,69,70,72,72,69,68,70,73,63,59 1,61,60,60,62,64,72,68,67,74,68,76,70,74,71,76,74,74,70,75,66,69,62,65,60,66,65,68,59,64,59,72,65,55,56,66,66,66,60,60,58,60,67,49,52 1,65,62,67,68,65,67,71,71,64,56,73,72,68,69,56,57,67,62,74,66,80,76,80,78,53,47,48,36,68,65,74,73,60,60,67,63,74,63,77,79,68,70,59,56 1,74,73,72,79,66,61,76,66,65,64,78,74,62,57,48,36,62,50,67,63,79,70,61,57,52,36,69,49,55,65,74,73,58,60,64,62,73,69,62,67,60,56,53,46 1,70,69,60,62,58,60,71,77,69,69,73,68,68,70,69,65,76,75,63,64,67,74,56,60,54,44,68,69,68,68,74,73,61,59,68,67,64,68,64,76,64,61,54,49 1,67,66,65,77,66,70,72,72,72,67,76,72,73,76,74,71,74,73,69,61,78,70,76,73,70,70,62,51,70,68,79,77,75,68,72,71,69,63,65,61,73,73,64,67 1,76,69,78,73,68,67,75,70,77,70,79,73,79,75,74,71,76,68,81,79,77,78,75,76,66,76,65,67,67,57,68,75,50,62,62,59,47,49,75,65,74,70,51,48 1,70,69,67,66,68,60,76,77,70,67,71,71,79,79,70,64,77,76,63,54,68,65,72,67,59,52,56,50,67,61,74,72,67,59,68,66,73,68,74,68,77,69,65,62 1,78,73,68,74,68,69,63,74,68,67,73,73,66,71,64,67,66,68,61,66,75,71,60,62,64,66,65,67,66,62,74,75,61,61,63,66,68,65,71,62,69,67,61,59 1,67,51,73,65,69,56,72,63,64,56,68,67,70,62,70,58,68,62,65,59,77,69,68,59,64,55,65,60,70,60,72,65,58,51,66,59,71,62,74,60,76,65,62,56 1,70,54,66,66,76,46,74,58,68,52,81,58,67,58,68,32,73,59,76,51,82,57,76,54,58,30,69,41,59,59,67,73,62,55,60,55,65,56,65,44,73,36,51,28 1,63,63,69,72,67,62,65,57,68,53,68,71,73,78,64,58,61,54,70,61,72,67,72,68,57,55,61,53,66,60,76,77,73,66,66,58,75,70,77,67,78,68,64,58 1,62,56,66,57,74,75,68,59,65,59,74,66,71,65,67,69,66,66,71,72,80,74,71,63,62,72,62,66,66,61,73,68,59,59,63,62,73,73,76,67,77,71,62,58 1,80,74,82,77,74,74,73,77,64,61,73,73,73,72,62,66,66,68,63,61,69,75,70,75,59,64,63,69,66,66,70,77,62,62,60,65,67,66,74,71,66,71,59,62 1,63,58,66,55,56,58,69,74,44,48,63,60,76,67,73,73,58,66,68,63,72,74,70,72,77,75,70,71,71,67,75,73,60,59,71,70,65,62,70,69,71,70,58,61 1,70,65,65,62,68,67,77,74,62,61,66,61,69,74,64,62,71,71,74,70,77,78,69,70,67,65,67,70,49,48,73,71,65,73,73,73,75,71,73,72,73,70,65,64 1,61,63,58,62,56,60,67,75,61,57,64,71,56,59,66,62,73,76,71,75,83,84,69,71,69,69,69,71,49,43,59,64,56,61,64,72,70,73,69,70,65,68,65,62 1,70,64,52,58,75,89,70,72,26,30,46,55,54,59,40,40,39,37,35,17,59,52,66,72,23,46,8,31,17,20,49,72,61,70,31,13,40,23,31,30,57,67,41,57 1,75,71,54,51,53,50,68,69,46,55,11,12,43,48,61,60,73,77,46,45,68,59,65,73,54,60,55,66,54,41,53,52,58,63,72,65,33,23,64,54,36,46,45,52 1,77,61,62,68,62,58,72,68,77,71,76,77,72,75,62,57,77,74,61,58,72,76,69,68,56,53,57,54,69,70,73,79,65,70,66,68,67,66,71,67,60,60,53,57 1,75,72,75,79,72,68,79,77,69,66,73,77,67,73,57,58,69,69,67,65,77,68,69,65,58,54,68,60,67,66,75,78,63,66,68,64,72,69,73,61,52,44,34,37 1,78,76,71,72,65,71,75,74,70,64,65,76,65,73,59,57,65,65,73,73,81,80,68,66,59,44,62,63,62,59,71,74,59,60,64,61,77,76,62,67,44,42,44,30 1,69,68,75,74,78,72,75,72,61,57,72,71,75,72,70,68,68,62,62,66,67,67,74,78,64,68,62,62,64,63,75,77,66,67,69,65,62,63,64,59,74,75,63,67 1,72,66,75,67,61,59,64,63,61,67,75,76,66,48,61,56,69,68,68,68,68,75,69,67,68,71,70,68,48,47,74,79,63,75,62,62,64,67,56,52,69,83,59,73 1,64,64,70,75,70,71,74,71,59,60,62,68,70,66,69,72,69,69,61,63,56,60,62,66,69,71,62,63,67,65,62,58,52,51,67,66,61,56,64,65,71,73,57,63 1,72,63,68,62,72,63,79,61,57,49,76,75,55,57,43,37,54,52,57,56,78,78,57,55,35,37,57,57,41,35,67,70,75,72,53,46,63,62,53,43,38,35,32,26 1,79,78,66,63,69,62,78,70,72,71,73,78,75,65,68,62,76,71,68,68,72,71,52,48,23,26,66,59,66,66,72,74,56,58,67,63,66,69,70,74,34,33,11,12 1,66,81,75,72,69,67,74,81,67,73,76,75,69,64,58,57,74,74,56,62,74,78,55,50,37,38,65,73,61,61,73,73,61,63,67,66,60,71,46,58,35,37,24,20 1,65,66,71,72,67,75,76,83,70,74,70,76,70,68,63,71,69,76,72,73,76,80,69,68,57,59,59,56,62,68,75,73,65,61,69,73,66,70,63,65,65,67,53,42 1,71,75,76,74,71,68,67,68,69,75,75,74,59,58,71,69,70,74,74,72,71,78,69,72,69,72,63,61,59,70,72,75,61,66,70,71,59,64,64,60,72,61,55,63 1,70,66,66,68,71,69,64,61,68,67,50,53,73,71,73,63,71,73,80,81,82,82,67,71,52,47,67,64,66,67,66,75,58,62,65,65,71,67,70,71,67,64,52,53 1,73,76,68,74,56,59,73,76,54,48,75,78,47,53,25,19,60,56,56,54,80,79,47,53,19,14,58,50,67,71,63,54,49,48,66,65,62,58,57,72,31,30,15,11 1,68,76,79,78,63,73,68,78,64,71,73,77,67,71,58,57,61,63,52,64,64,74,53,72,36,44,52,54,49,56,73,81,65,80,53,60,63,70,58,64,52,57,49,50 1,68,64,65,68,63,64,77,73,75,72,80,77,70,71,61,61,73,68,63,62,76,73,69,69,48,59,62,44,66,59,75,74,64,64,63,61,70,69,74,67,51,48,45,45 0,62,67,64,70,59,58,67,74,60,66,68,68,73,71,60,63,64,74,64,65,74,77,69,73,59,58,58,67,65,69,78,76,61,62,64,67,72,74,71,71,71,69,66,61 0,62,67,68,70,65,70,73,77,69,70,69,73,71,74,71,71,76,75,66,67,73,73,70,74,63,67,58,68,66,69,78,79,69,70,71,73,72,71,73,77,72,76,64,66 0,59,68,69,67,69,59,78,73,66,65,77,73,74,66,66,55,71,66,69,68,75,73,80,79,69,65,69,66,68,65,75,71,59,61,65,64,73,71,81,75,74,65,69,66 0,75,75,70,77,67,75,75,75,67,66,74,73,68,72,64,70,76,70,67,63,74,75,72,68,69,68,75,69,71,74,75,76,63,70,71,69,66,63,70,73,66,68,58,59 0,77,79,79,77,74,76,76,81,65,68,66,66,74,73,72,68,67,73,63,62,72,67,76,69,68,64,64,61,69,68,73,75,70,66,64,70,70,70,73,76,79,73,65,63 0,68,64,74,80,76,72,78,75,67,64,75,80,78,77,66,64,67,67,70,60,78,82,70,68,63,60,64,60,54,56,70,73,59,65,55,58,50,51,73,70,69,65,42,41 0,76,73,74,76,60,69,76,76,68,69,78,79,57,62,69,69,67,66,73,69,80,81,58,68,75,69,73,70,58,65,79,76,74,71,66,64,65,62,78,68,75,68,62,60 0,61,76,71,68,77,69,77,69,64,75,71,81,75,72,71,69,70,73,61,71,69,79,64,65,62,66,61,65,71,68,67,71,59,64,66,65,60,68,74,71,69,68,63,59 0,67,65,77,74,67,66,67,70,65,64,75,78,66,74,62,60,65,65,73,72,75,76,74,81,66,65,65,63,63,67,76,80,63,64,63,64,73,72,76,75,72,74,65,64 0,71,61,74,74,76,74,69,56,68,78,71,78,58,64,70,72,71,68,72,71,79,78,67,68,63,60,67,67,76,74,67,79,67,71,71,64,70,74,83,76,74,73,54,54 0,64,70,71,69,72,70,75,78,61,66,69,68,68,70,71,70,75,76,73,72,80,78,79,81,74,70,72,79,73,75,77,73,65,64,72,72,59,62,71,74,68,67,58,57 0,76,75,68,78,71,72,72,75,61,65,67,70,67,75,60,58,63,67,59,63,67,72,74,73,56,56,52,52,67,68,73,78,65,68,61,67,69,74,77,75,74,70,63,61 0,74,73,72,75,63,62,67,67,73,74,75,79,70,71,64,67,65,69,79,78,81,80,71,73,60,62,69,67,69,69,75,75,66,67,67,66,71,73,66,69,62,65,55,56 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