% 1. Title: Pima Indians Diabetes Database % % 2. Sources: % (a) Original owners: National Institute of Diabetes and Digestive and % Kidney Diseases % (b) Donor of database: Vincent Sigillito (vgs@aplcen.apl.jhu.edu) % Research Center, RMI Group Leader % Applied Physics Laboratory % The Johns Hopkins University % Johns Hopkins Road % Laurel, MD 20707 % (301) 953-6231 % (c) Date received: 9 May 1990 % % 3. Past Usage: % 1. Smith,~J.~W., Everhart,~J.~E., Dickson,~W.~C., Knowler,~W.~C., \& % Johannes,~R.~S. (1988). Using the ADAP learning algorithm to forecast % the onset of diabetes mellitus. In {\it Proceedings of the Symposium % on Computer Applications and Medical Care} (pp. 261--265). IEEE % Computer Society Press. % % The diagnostic, binary-valued variable investigated is whether the % patient shows signs of diabetes according to World Health Organization % criteria (i.e., if the 2 hour post-load plasma glucose was at least % 200 mg/dl at any survey examination or if found during routine medical % care). The population lives near Phoenix, Arizona, USA. % % Results: Their ADAP algorithm makes a real-valued prediction between % 0 and 1. This was transformed into a binary decision using a cutoff of % 0.448. Using 576 training instances, the sensitivity and specificity % of their algorithm was 76% on the remaining 192 instances. % % 4. Relevant Information: % Several constraints were placed on the selection of these instances from % a larger database. In particular, all patients here are females at % least 21 years old of Pima Indian heritage. ADAP is an adaptive learning % routine that generates and executes digital analogs of perceptron-like % devices. It is a unique algorithm; see the paper for details. % % 5. Number of Instances: 768 % % 6. Number of Attributes: 8 plus class % % 7. For Each Attribute: (all numeric-valued) % 1. Number of times pregnant % 2. Plasma glucose concentration a 2 hours in an oral glucose tolerance test % 3. Diastolic blood pressure (mm Hg) % 4. Triceps skin fold thickness (mm) % 5. 2-Hour serum insulin (mu U/ml) % 6. Body mass index (weight in kg/(height in m)^2) % 7. Diabetes pedigree function % 8. Age (years) % 9. Class variable (0 or 1) % % 8. Missing Attribute Values: None % % 9. Class Distribution: (class value 1 is interpreted as "tested positive for % diabetes") % % Class Value Number of instances % 0 500 % 1 268 % % 10. Brief statistical analysis: % % Attribute number: Mean: Standard Deviation: % 1. 3.8 3.4 % 2. 120.9 32.0 % 3. 69.1 19.4 % 4. 20.5 16.0 % 5. 79.8 115.2 % 6. 32.0 7.9 % 7. 0.5 0.3 % 8. 33.2 11.8 % % % % % % % Relabeled values in attribute 'class' % From: 0 To: tested_negative % From: 1 To: tested_positive % @relation pima_diabetes @attribute 'preg' real @attribute 'plas' real @attribute 'pres' real @attribute 'skin' real @attribute 'insu' real @attribute 'mass' real @attribute 'pedi' real @attribute 'age' real @attribute 'class' {tested_negative,tested_positive} @data 10,161,68,23,132,25.5,0.326,47,tested_positive 7,109,80,31,0,35.9,1.127,43,tested_positive 0,128,68,19,180,30.5,1.391,25,tested_positive 2,155,52,27,540,38.7,0.24,25,tested_positive 4,111,72,47,207,37.1,1.39,56,tested_positive 3,170,64,37,225,34.5,0.356,30,tested_positive 1,189,60,23,846,30.1,0.398,59,tested_positive 2,197,70,45,543,30.5,0.158,53,tested_positive 0,179,50,36,159,37.8,0.455,22,tested_positive 9,164,78,0,0,32.8,0.148,45,tested_positive 5,116,74,29,0,32.3,0.66,35,tested_positive 2,197,70,99,0,34.7,0.575,62,tested_positive 5,139,80,35,160,31.6,0.361,25,tested_positive 4,171,72,0,0,43.6,0.479,26,tested_positive 2,108,80,0,0,27,0.259,52,tested_positive 1,149,68,29,127,29.3,0.349,42,tested_positive 8,196,76,29,280,37.5,0.605,57,tested_positive 6,102,82,0,0,30.8,0.18,36,tested_positive 1,168,88,29,0,35,0.905,52,tested_positive 8,100,74,40,215,39.4,0.661,43,tested_positive 13,104,72,0,0,31.2,0.465,38,tested_positive 4,158,78,0,0,32.9,0.803,31,tested_positive 0,151,90,46,0,42.1,0.371,21,tested_positive 6,162,62,0,0,24.3,0.178,50,tested_positive 5,115,76,0,0,31.2,0.343,44,tested_positive 7,160,54,32,175,30.5,0.588,39,tested_positive 0,102,64,46,78,40.6,0.496,21,tested_negative 7,124,70,33,215,25.5,0.161,37,tested_negative 13,106,70,0,0,34.2,0.251,52,tested_negative 12,88,74,40,54,35.3,0.378,48,tested_negative 0,137,70,38,0,33.2,0.17,22,tested_negative 3,128,78,0,0,21.1,0.268,55,tested_negative 1,138,82,0,0,40.1,0.236,28,tested_negative 10,115,98,0,0,24,1.022,34,tested_negative 2,105,75,0,0,23.3,0.56,53,tested_negative 2,101,58,17,265,24.2,0.614,23,tested_negative 2,112,78,50,140,39.4,0.175,24,tested_negative 1,109,60,8,182,25.4,0.947,21,tested_negative 0,73,0,0,0,21.1,0.342,25,tested_negative 3,106,54,21,158,30.9,0.292,24,tested_negative 1,106,70,28,135,34.2,0.142,22,tested_negative 6,105,70,32,68,30.8,0.122,37,tested_negative 2,83,66,23,50,32.2,0.497,22,tested_negative 0,57,60,0,0,21.7,0.735,67,tested_negative 9,72,78,25,0,31.6,0.28,38,tested_negative 3,78,70,0,0,32.5,0.27,39,tested_negative 7,150,66,42,342,34.7,0.718,42,tested_negative 5,123,74,40,77,34.1,0.269,28,tested_negative 4,103,60,33,192,24,0.966,33,tested_negative 2,115,64,22,0,30.8,0.421,21,tested_negative 0,101,65,28,0,24.6,0.237,22,tested_negative 0,125,68,0,0,24.7,0.206,21,tested_negative 1,103,80,11,82,19.4,0.491,22,tested_negative 1,97,70,40,0,38.1,0.218,30,tested_negative 1,109,58,18,116,28.5,0.219,22,tested_negative 3,148,66,25,0,32.5,0.256,22,tested_negative 1,153,82,42,485,40.6,0.687,23,tested_negative 3,96,78,39,0,37.3,0.238,40,tested_negative 1,105,58,0,0,24.3,0.187,21,tested_negative 0,93,60,25,92,28.7,0.532,22,tested_negative 0,147,85,54,0,42.8,0.375,24,tested_negative 0,100,88,60,110,46.8,0.962,31,tested_negative 5,104,74,0,0,28.8,0.153,48,tested_negative 2,87,0,23,0,28.9,0.773,25,tested_negative 0,107,76,0,0,45.3,0.686,24,tested_negative 1,112,72,30,176,34.4,0.528,25,tested_negative 1,144,82,40,0,41.3,0.607,28,tested_negative 7,114,76,17,110,23.8,0.466,31,tested_negative 0,124,56,13,105,21.8,0.452,21,tested_negative 4,154,72,29,126,31.3,0.338,37,tested_negative 1,97,66,15,140,23.2,0.487,22,tested_negative 1,91,54,25,100,25.2,0.234,23,tested_negative 2,95,54,14,88,26.1,0.748,22,tested_negative 7,142,60,33,190,28.8,0.687,61,tested_negative 2,100,68,25,71,38.5,0.324,26,tested_negative 0,99,0,0,0,25,0.253,22,tested_negative 7,97,76,32,91,40.9,0.871,32,tested_positive