% 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 0,189,104,25,0,34.3,0.435,41,tested_positive 3,139,54,0,0,25.6,0.402,22,tested_positive 0,113,76,0,0,33.3,0.278,23,tested_positive 8,176,90,34,300,33.7,0.467,58,tested_positive 0,123,72,0,0,36.3,0.258,52,tested_positive 8,186,90,35,225,34.5,0.423,37,tested_positive 8,120,0,0,0,30,0.183,38,tested_positive 1,128,88,39,110,36.5,1.057,37,tested_positive 6,148,72,35,0,33.6,0.627,50,tested_positive 9,140,94,0,0,32.7,0.734,45,tested_positive 0,138,0,0,0,36.3,0.933,25,tested_positive 3,193,70,31,0,34.9,0.241,25,tested_positive 3,130,78,23,79,28.4,0.323,34,tested_positive 0,118,84,47,230,45.8,0.551,31,tested_positive 3,107,62,13,48,22.9,0.678,23,tested_positive 1,102,74,0,0,39.5,0.293,42,tested_positive 9,119,80,35,0,29,0.263,29,tested_positive 3,174,58,22,194,32.9,0.593,36,tested_positive 2,93,64,32,160,38,0.674,23,tested_positive 8,133,72,0,0,32.9,0.27,39,tested_positive 5,85,74,22,0,29,1.224,32,tested_positive 5,144,82,26,285,32,0.452,58,tested_positive 8,124,76,24,600,28.7,0.687,52,tested_positive 9,112,82,32,175,34.2,0.26,36,tested_positive 8,188,78,0,0,47.9,0.137,43,tested_positive 5,130,82,0,0,39.1,0.956,37,tested_positive 2,81,72,15,76,30.1,0.547,25,tested_negative 2,129,84,0,0,28,0.284,27,tested_negative 2,87,0,23,0,28.9,0.773,25,tested_negative 4,117,64,27,120,33.2,0.23,24,tested_negative 1,124,74,36,0,27.8,0.1,30,tested_negative 0,84,82,31,125,38.2,0.233,23,tested_negative 4,92,80,0,0,42.2,0.237,29,tested_negative 0,135,94,46,145,40.6,0.284,26,tested_negative 6,80,66,30,0,26.2,0.313,41,tested_negative 6,111,64,39,0,34.2,0.26,24,tested_negative 2,108,64,0,0,30.8,0.158,21,tested_negative 3,99,62,19,74,21.8,0.279,26,tested_negative 1,79,75,30,0,32,0.396,22,tested_negative 10,133,68,0,0,27,0.245,36,tested_negative 4,110,92,0,0,37.6,0.191,30,tested_negative 4,129,60,12,231,27.5,0.527,31,tested_negative 4,84,90,23,56,39.5,0.159,25,tested_negative 5,88,66,21,23,24.4,0.342,30,tested_negative 6,129,90,7,326,19.6,0.582,60,tested_negative 6,93,50,30,64,28.7,0.356,23,tested_negative 1,0,68,35,0,32,0.389,22,tested_negative 3,106,54,21,158,30.9,0.292,24,tested_negative 2,112,68,22,94,34.1,0.315,26,tested_negative 3,148,66,25,0,32.5,0.256,22,tested_negative 5,108,72,43,75,36.1,0.263,33,tested_negative 0,93,60,25,92,28.7,0.532,22,tested_negative 2,106,56,27,165,29,0.426,22,tested_negative 8,65,72,23,0,32,0.6,42,tested_negative 2,112,78,50,140,39.4,0.175,24,tested_negative 1,193,50,16,375,25.9,0.655,24,tested_negative 0,86,68,32,0,35.8,0.238,25,tested_negative 1,93,56,11,0,22.5,0.417,22,tested_negative 2,92,76,20,0,24.2,1.698,28,tested_negative 1,83,68,0,0,18.2,0.624,27,tested_negative 2,112,86,42,160,38.4,0.246,28,tested_negative 5,114,74,0,0,24.9,0.744,57,tested_negative 0,97,64,36,100,36.8,0.6,25,tested_negative 1,111,62,13,182,24,0.138,23,tested_negative 2,84,0,0,0,0,0.304,21,tested_negative 1,151,60,0,0,26.1,0.179,22,tested_negative 9,134,74,33,60,25.9,0.46,81,tested_negative 4,154,72,29,126,31.3,0.338,37,tested_negative 4,91,70,32,88,33.1,0.446,22,tested_negative 2,99,0,0,0,22.2,0.108,23,tested_negative 1,90,68,8,0,24.5,1.138,36,tested_negative 5,117,86,30,105,39.1,0.251,42,tested_negative 8,100,76,0,0,38.7,0.19,42,tested_negative 2,157,74,35,440,39.4,0.134,30,tested_negative 1,95,74,21,73,25.9,0.673,36,tested_negative 1,85,66,29,0,26.6,0.351,31,tested_negative 3,121,52,0,0,36,0.127,25,tested_positive 8,109,76,39,114,27.9,0.64,31,tested_positive