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Uni Köln
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Mosler > Prof. Mosler > Datenportal
Datenportal des Lehrstuhls für Statistik und Ökonometrie
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PIMA (training) data
The data set (and description) can be downloaded here:
http://www.stats.ox.ac.uk/pub/PRNN/pima.tr
Description:
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: Yes
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
Descriptive statistics:
Dataset= pima : n= 200 , d= 7
Class1: n= 132
Covariance matrix:
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 7.8785 10.7723 8.1908 2.9103 -0.0358 -0.2073 16.8289
[2,] 10.7723 709.5612 81.4303 13.2377 19.0379 -0.5186 59.0131
[3,] 8.1908 81.4303 122.8452 33.8799 16.6126 -0.0772 46.7870
[4,] 2.9103 13.2377 33.8799 119.4464 50.1259 0.0743 18.4707
[5,] -0.0358 19.0379 16.6126 50.1259 40.7230 0.1452 7.0000
[6,] -0.2073 -0.5186 -0.0772 0.0743 0.1452 0.0714 -0.5381
[7,] 16.8289 59.0131 46.7870 18.4707 7.0000 -0.5381 91.0818
Correlation matrix:
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.0000 0.1441 0.2633 0.0949 -0.0020 -0.2765 0.6282
[2,] 0.1441 1.0000 0.2758 0.0455 0.1120 -0.0729 0.2321
[3,] 0.2633 0.2758 1.0000 0.2797 0.2349 -0.0261 0.4423
[4,] 0.0949 0.0455 0.2797 1.0000 0.7187 0.0254 0.1771
[5,] -0.0020 0.1120 0.2349 0.7187 1.0000 0.0852 0.1149
[6,] -0.2765 -0.0729 -0.0261 0.0254 0.0852 1.0000 -0.2110
[7,] 0.6282 0.2321 0.4423 0.1771 0.1149 -0.2110 1.0000
Median: 2.5968 110.4798 68.5842 26.3021 30.9338 0.4076 27.3908
Mean: 2.9167 113.1061 69.5455 27.2045 31.0742 0.4155 29.2348
MCD-estimated:
MDC-0.975-Mean: 1.9579 107.7895 67.4 25.3474 30.6074 0.4068 24.7263
MDC-0.750-Mean: 1.9579 107.7895 67.4 25.3474 30.6074 0.4068 24.7263
MDC-0.500-Mean: 1.8602 107.6882 67.3441 25.2903 30.6419 0.4078 24.6667
Class2: n= 68
Covariance matrix:
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 15.7794 -8.1993 6.4249 -0.5180 -1.0329 -0.1330 21.9344
[2,] -8.1993 907.2502 23.7112 87.5154 9.9816 -0.0822 58.1229
[3,] 6.4249 23.7112 134.1861 19.7059 5.1589 -0.7955 26.3038
[4,] -0.5180 87.5154 19.7059 151.3292 28.2855 0.3480 26.6787
[5,] -1.0329 9.9816 5.1589 28.2855 23.1453 0.4577 -7.9122
[6,] -0.1330 -0.0822 -0.7955 0.3480 0.4577 0.1289 -0.4174
[7,] 21.9344 58.1229 26.3038 26.6787 -7.9122 -0.4174 131.7987
Correlation matrix:
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.0000 -0.0685 0.1396 -0.0106 -0.0540 -0.0933 0.4810
[2,] -0.0685 1.0000 0.0680 0.2362 0.0689 -0.0076 0.1681
[3,] 0.1396 0.0680 1.0000 0.1383 0.0926 -0.1913 0.1978
[4,] -0.0106 0.2362 0.1383 1.0000 0.4779 0.0788 0.1889
[5,] -0.0540 0.0689 0.0926 0.4779 1.0000 0.2650 -0.1433
[6,] -0.0933 -0.0076 -0.1913 0.0788 0.2650 1.0000 -0.1013
[7,] 0.4810 0.1681 0.1978 0.1889 -0.1433 -0.1013 1.0000
Median: 5.1258 144.4749 74.9284 33.0938 34.7369 0.5428 37.4477
Mean: 4.8382 145.0588 74.5882 33.1176 34.7088 0.5487 37.6912
MCD-estimated:
MDC-0.975-Mean: 5.4737 144.3509 74.386 32.193 34.1404 0.499 38.1053
MDC-0.750-Mean: 5.2778 143.9259 75.1111 32.8704 34.3463 0.4983 37.6111
MDC-0.500-Mean: 5.0847 144.1186 75.4576 32.1695 34.4593 0.4867 37.0169
Measures:
Mah.Dist: 1.5192
Mah.Dist-MCD-0.975: 2.1257
Mah.Dist-MCD-0.750: 2.2001
Mah.Dist-MCD-0.500: 2.1567
Zuletzt geändert am 17.02.2013
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