Upload diabetes.arff

diabetes.arff

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+% 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
+6,148,72,35,0,33.6,0.627,50,tested_positive
+1,85,66,29,0,26.6,0.351,31,tested_negative
+8,183,64,0,0,23.3,0.672,32,tested_positive
+1,89,66,23,94,28.1,0.167,21,tested_negative
+0,137,40,35,168,43.1,2.288,33,tested_positive
+5,116,74,0,0,25.6,0.201,30,tested_negative
+3,78,50,32,88,31,0.248,26,tested_positive
+10,115,0,0,0,35.3,0.134,29,tested_negative
+2,197,70,45,543,30.5,0.158,53,tested_positive
+8,125,96,0,0,0,0.232,54,tested_positive
+4,110,92,0,0,37.6,0.191,30,tested_negative
+10,168,74,0,0,38,0.537,34,tested_positive
+10,139,80,0,0,27.1,1.441,57,tested_negative
+1,189,60,23,846,30.1,0.398,59,tested_positive
+5,166,72,19,175,25.8,0.587,51,tested_positive
+7,100,0,0,0,30,0.484,32,tested_positive
+0,118,84,47,230,45.8,0.551,31,tested_positive
+7,107,74,0,0,29.6,0.254,31,tested_positive
+1,103,30,38,83,43.3,0.183,33,tested_negative
+1,115,70,30,96,34.6,0.529,32,tested_positive
+3,126,88,41,235,39.3,0.704,27,tested_negative
+8,99,84,0,0,35.4,0.388,50,tested_negative
+7,196,90,0,0,39.8,0.451,41,tested_positive
+9,119,80,35,0,29,0.263,29,tested_positive
+11,143,94,33,146,36.6,0.254,51,tested_positive
+10,125,70,26,115,31.1,0.205,41,tested_positive
+7,147,76,0,0,39.4,0.257,43,tested_positive
+1,97,66,15,140,23.2,0.487,22,tested_negative
+13,145,82,19,110,22.2,0.245,57,tested_negative
+5,117,92,0,0,34.1,0.337,38,tested_negative
+5,109,75,26,0,36,0.546,60,tested_negative
+3,158,76,36,245,31.6,0.851,28,tested_positive
+3,88,58,11,54,24.8,0.267,22,tested_negative
+6,92,92,0,0,19.9,0.188,28,tested_negative
+10,122,78,31,0,27.6,0.512,45,tested_negative
+4,103,60,33,192,24,0.966,33,tested_negative
+11,138,76,0,0,33.2,0.42,35,tested_negative
+9,102,76,37,0,32.9,0.665,46,tested_positive
+2,90,68,42,0,38.2,0.503,27,tested_positive
+4,111,72,47,207,37.1,1.39,56,tested_positive
+3,180,64,25,70,34,0.271,26,tested_negative
+7,133,84,0,0,40.2,0.696,37,tested_negative
+7,106,92,18,0,22.7,0.235,48,tested_negative
+9,171,110,24,240,45.4,0.721,54,tested_positive
+7,159,64,0,0,27.4,0.294,40,tested_negative
+0,180,66,39,0,42,1.893,25,tested_positive
+1,146,56,0,0,29.7,0.564,29,tested_negative
+2,71,70,27,0,28,0.586,22,tested_negative
+7,103,66,32,0,39.1,0.344,31,tested_positive
+7,105,0,0,0,0,0.305,24,tested_negative
+1,103,80,11,82,19.4,0.491,22,tested_negative
+1,101,50,15,36,24.2,0.526,26,tested_negative
+5,88,66,21,23,24.4,0.342,30,tested_negative
+8,176,90,34,300,33.7,0.467,58,tested_positive
+7,150,66,42,342,34.7,0.718,42,tested_negative
+1,73,50,10,0,23,0.248,21,tested_negative
+7,187,68,39,304,37.7,0.254,41,tested_positive
+0,100,88,60,110,46.8,0.962,31,tested_negative
+0,146,82,0,0,40.5,1.781,44,tested_negative
+0,105,64,41,142,41.5,0.173,22,tested_negative
+2,84,0,0,0,0,0.304,21,tested_negative
+8,133,72,0,0,32.9,0.27,39,tested_positive
+5,44,62,0,0,25,0.587,36,tested_negative
+2,141,58,34,128,25.4,0.699,24,tested_negative
+7,114,66,0,0,32.8,0.258,42,tested_positive
+5,99,74,27,0,29,0.203,32,tested_negative
+0,109,88,30,0,32.5,0.855,38,tested_positive
+2,109,92,0,0,42.7,0.845,54,tested_negative
+1,95,66,13,38,19.6,0.334,25,tested_negative
+4,146,85,27,100,28.9,0.189,27,tested_negative
+2,100,66,20,90,32.9,0.867,28,tested_positive
+5,139,64,35,140,28.6,0.411,26,tested_negative
+13,126,90,0,0,43.4,0.583,42,tested_positive
+4,129,86,20,270,35.1,0.231,23,tested_negative
+1,79,75,30,0,32,0.396,22,tested_negative
+1,0,48,20,0,24.7,0.14,22,tested_negative
+7,62,78,0,0,32.6,0.391,41,tested_negative
+5,95,72,33,0,37.7,0.37,27,tested_negative
+0,131,0,0,0,43.2,0.27,26,tested_positive
+2,112,66,22,0,25,0.307,24,tested_negative
+3,113,44,13,0,22.4,0.14,22,tested_negative
+2,74,0,0,0,0,0.102,22,tested_negative
+7,83,78,26,71,29.3,0.767,36,tested_negative
+0,101,65,28,0,24.6,0.237,22,tested_negative
+5,137,108,0,0,48.8,0.227,37,tested_positive
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+4,123,80,15,176,32,0.443,34,tested_negative
+7,81,78,40,48,46.7,0.261,42,tested_negative
+4,134,72,0,0,23.8,0.277,60,tested_positive
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+6,144,72,27,228,33.9,0.255,40,tested_negative
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+1,71,48,18,76,20.4,0.323,22,tested_negative
+6,93,50,30,64,28.7,0.356,23,tested_negative
+1,122,90,51,220,49.7,0.325,31,tested_positive
+1,163,72,0,0,39,1.222,33,tested_positive
+1,151,60,0,0,26.1,0.179,22,tested_negative
+0,125,96,0,0,22.5,0.262,21,tested_negative
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+1,126,56,29,152,28.7,0.801,21,tested_negative
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+4,144,58,28,140,29.5,0.287,37,tested_negative
+3,83,58,31,18,34.3,0.336,25,tested_negative
+0,95,85,25,36,37.4,0.247,24,tested_positive
+3,171,72,33,135,33.3,0.199,24,tested_positive
+8,155,62,26,495,34,0.543,46,tested_positive
+1,89,76,34,37,31.2,0.192,23,tested_negative
+4,76,62,0,0,34,0.391,25,tested_negative
+7,160,54,32,175,30.5,0.588,39,tested_positive
+4,146,92,0,0,31.2,0.539,61,tested_positive
+5,124,74,0,0,34,0.22,38,tested_positive
+5,78,48,0,0,33.7,0.654,25,tested_negative
+4,97,60,23,0,28.2,0.443,22,tested_negative
+4,99,76,15,51,23.2,0.223,21,tested_negative
+0,162,76,56,100,53.2,0.759,25,tested_positive
+6,111,64,39,0,34.2,0.26,24,tested_negative
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+5,132,80,0,0,26.8,0.186,69,tested_negative
+0,113,76,0,0,33.3,0.278,23,tested_positive
+1,88,30,42,99,55,0.496,26,tested_positive
+3,120,70,30,135,42.9,0.452,30,tested_negative
+1,118,58,36,94,33.3,0.261,23,tested_negative
+1,117,88,24,145,34.5,0.403,40,tested_positive
+0,105,84,0,0,27.9,0.741,62,tested_positive
+4,173,70,14,168,29.7,0.361,33,tested_positive
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+5,106,82,30,0,39.5,0.286,38,tested_negative
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+10,108,66,0,0,32.4,0.272,42,tested_positive
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+9,57,80,37,0,32.8,0.096,41,tested_negative
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+9,156,86,28,155,34.3,1.189,42,tested_positive
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+8,188,78,0,0,47.9,0.137,43,tested_positive
+7,152,88,44,0,50,0.337,36,tested_positive
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+17,163,72,41,114,40.9,0.817,47,tested_positive
+4,151,90,38,0,29.7,0.294,36,tested_negative
+7,102,74,40,105,37.2,0.204,45,tested_negative
+0,114,80,34,285,44.2,0.167,27,tested_negative
+2,100,64,23,0,29.7,0.368,21,tested_negative
+0,131,88,0,0,31.6,0.743,32,tested_positive
+6,104,74,18,156,29.9,0.722,41,tested_positive
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+6,102,82,0,0,30.8,0.18,36,tested_positive
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+8,179,72,42,130,32.7,0.719,36,tested_positive
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+4,141,74,0,0,27.6,0.244,40,tested_negative
+7,194,68,28,0,35.9,0.745,41,tested_positive
+8,181,68,36,495,30.1,0.615,60,tested_positive
+1,128,98,41,58,32,1.321,33,tested_positive
+8,109,76,39,114,27.9,0.64,31,tested_positive
+5,139,80,35,160,31.6,0.361,25,tested_positive
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+7,159,66,0,0,30.4,0.383,36,tested_positive
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+4,109,64,44,99,34.8,0.905,26,tested_positive
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+8,196,76,29,280,37.5,0.605,57,tested_positive
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+5,85,74,22,0,29,1.224,32,tested_positive
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+3,162,52,38,0,37.2,0.652,24,tested_positive
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+4,142,86,0,0,44,0.645,22,tested_positive
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+9,164,84,21,0,30.8,0.831,32,tested_positive
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+3,139,54,0,0,25.6,0.402,22,tested_positive
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+9,184,85,15,0,30,1.213,49,tested_positive
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+12,92,62,7,258,27.6,0.926,44,tested_positive
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+11,155,76,28,150,33.3,1.353,51,tested_positive
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+0,138,0,0,0,36.3,0.933,25,tested_positive
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