% 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 1,115,70,30,96,34.6,0.529,32,tested_positive 10,90,85,32,0,34.9,0.825,56,tested_positive 0,137,40,35,168,43.1,2.288,33,tested_positive 9,156,86,0,0,24.8,0.23,53,tested_positive 6,119,50,22,176,27.1,1.318,33,tested_positive 0,128,68,19,180,30.5,1.391,25,tested_positive 10,111,70,27,0,27.5,0.141,40,tested_positive 4,184,78,39,277,37,0.264,31,tested_positive 8,167,106,46,231,37.6,0.165,43,tested_positive 4,134,72,0,0,23.8,0.277,60,tested_positive 12,140,82,43,325,39.2,0.528,58,tested_positive 10,115,0,0,0,0,0.261,30,tested_positive 10,101,86,37,0,45.6,1.136,38,tested_positive 8,197,74,0,0,25.9,1.191,39,tested_positive 5,139,80,35,160,31.6,0.361,25,tested_positive 2,105,80,45,191,33.7,0.711,29,tested_positive 7,194,68,28,0,35.9,0.745,41,tested_positive 0,180,78,63,14,59.4,2.42,25,tested_positive 7,114,64,0,0,27.4,0.732,34,tested_positive 0,141,0,0,0,42.4,0.205,29,tested_positive 10,161,68,23,132,25.5,0.326,47,tested_positive 10,108,66,0,0,32.4,0.272,42,tested_positive 6,125,78,31,0,27.6,0.565,49,tested_positive 11,138,74,26,144,36.1,0.557,50,tested_positive 8,196,76,29,280,37.5,0.605,57,tested_positive 4,148,60,27,318,30.9,0.15,29,tested_positive 12,140,85,33,0,37.4,0.244,41,tested_negative 1,103,30,38,83,43.3,0.183,33,tested_negative 1,86,66,52,65,41.3,0.917,29,tested_negative 0,117,66,31,188,30.8,0.493,22,tested_negative 6,151,62,31,120,35.5,0.692,28,tested_negative 5,128,80,0,0,34.6,0.144,45,tested_negative 1,126,56,29,152,28.7,0.801,21,tested_negative 0,137,68,14,148,24.8,0.143,21,tested_negative 0,165,90,33,680,52.3,0.427,23,tested_negative 11,85,74,0,0,30.1,0.3,35,tested_negative 3,116,0,0,0,23.5,0.187,23,tested_negative 3,87,60,18,0,21.8,0.444,21,tested_negative 2,122,76,27,200,35.9,0.483,26,tested_negative 8,99,84,0,0,35.4,0.388,50,tested_negative 1,93,70,31,0,30.4,0.315,23,tested_negative 1,108,60,46,178,35.5,0.415,24,tested_negative 1,89,66,23,94,28.1,0.167,21,tested_negative 1,0,48,20,0,24.7,0.14,22,tested_negative 1,109,38,18,120,23.1,0.407,26,tested_negative 1,71,62,0,0,21.8,0.416,26,tested_negative 1,111,86,19,0,30.1,0.143,23,tested_negative 2,129,0,0,0,38.5,0.304,41,tested_negative 1,114,66,36,200,38.1,0.289,21,tested_negative 1,81,72,18,40,26.6,0.283,24,tested_negative 1,97,70,40,0,38.1,0.218,30,tested_negative 8,95,72,0,0,36.8,0.485,57,tested_negative 1,130,70,13,105,25.9,0.472,22,tested_negative 5,88,78,30,0,27.6,0.258,37,tested_negative 2,96,68,13,49,21.1,0.647,26,tested_negative 2,114,68,22,0,28.7,0.092,25,tested_negative 7,105,0,0,0,0,0.305,24,tested_negative 3,99,80,11,64,19.3,0.284,30,tested_negative 13,106,72,54,0,36.6,0.178,45,tested_negative 4,127,88,11,155,34.5,0.598,28,tested_negative 2,120,54,0,0,26.8,0.455,27,tested_negative 0,123,88,37,0,35.2,0.197,29,tested_negative 4,112,78,40,0,39.4,0.236,38,tested_negative 2,99,60,17,160,36.6,0.453,21,tested_negative 2,142,82,18,64,24.7,0.761,21,tested_negative 0,99,0,0,0,25,0.253,22,tested_negative 2,175,88,0,0,22.9,0.326,22,tested_negative 1,106,76,0,0,37.5,0.197,26,tested_negative 1,109,58,18,116,28.5,0.219,22,tested_negative 7,83,78,26,71,29.3,0.767,36,tested_negative 4,95,70,32,0,32.1,0.612,24,tested_negative 3,88,58,11,54,24.8,0.267,22,tested_negative 6,91,0,0,0,29.8,0.501,31,tested_negative 0,126,86,27,120,27.4,0.515,21,tested_negative 1,111,94,0,0,32.8,0.265,45,tested_negative 2,130,96,0,0,22.6,0.268,21,tested_negative 0,188,82,14,185,32,0.682,22,tested_positive