% 1. Title: Echocardiogram Data
%
% 2. Source Information:
%    -- Donor: Steven Salzberg (salzberg@cs.jhu.edu)
%    -- Collector:
%       -- Dr. Evlin Kinney
%       -- The Reed Institute
%       -- P.O. Box 402603
%       -- Maimi, FL 33140-0603
%    -- Date Received: 28 February 1989
%
% 3. Past Usage:
%    -- 1. Salzberg, S. (1988).  Exemplar-based learning: Theory and
%          implementation (Technical Report TR-10-88).  Harvard University,
%          Center for Research in Computing Technology, Aiken Computation
%          Laboratory (33 Oxford Street; Cambridge, MA 02138).
%       -- Steve applied his EACH program to predict survival (i.e., life
%          or death), did not use the wall-motion attribute, and recorded 87 
%          correct and 29 incorrect in an incremental application to this
%          database.  He also showed that, by tuning EACH to this domain,
%          EACH was able to derive (non-incrementally) a set of 28 
%          hyper-rectangles that could perfectly classify 119 instances.
%    -- 2. Kan, G., Visser, C., Kooler, J., & Dunning, A. (1986).  Short
%          and long term predictive value of wall motion score in acute 
%          myocardial infarction.  British Heart Journal, 56, 422-427.
%       -- They predicted the same variable (whether patients will live
%          one year after a heart attack) using a different set of 345
%          instances.  Their statistical test recorded a 61% accuracy
%          in predicting that a patient will die (post-hoc fit).
%    -- 3. Elvin Kinney (in communication with Steven Salzberg) reported
%          that a Cox regression application recorded a 60% accuracy
%          in predicting that a patient will die.
%
% 4. Relevant Information:
%   -- All the patients suffered heart attacks at some point in the past.
%      Some are still alive and some are not.  The survival and still-alive
%      variables, when taken together, indicate whether a patient survived
%      for at least one year following the heart attack.  
%
%      The problem addressed by past researchers was to predict from the 
%      other variables whether or not the patient will survive at least
%      one year.  The most difficult part of this problem is correctly
%      predicting that the patient will NOT survive.  (Part of the difficulty
%      seems to be the size of the data set.)
%
% 5. Number of Instances: 132
%
% 6. Number of Attributes: 13 (all numeric-valued)
%
% 7. Attribute Information:
%    1. survival -- the number of months patient survived (has survived,
% 		  if patient is still alive).  Because all the patients
% 		  had their heart attacks at different times, it is 
% 		  possible that some patients have survived less than
% 		  one year but they are still alive.  Check the second
% 		  variable to confirm this.  Such patients cannot be 
% 		  used for the prediction task mentioned above.
%    2. still-alive -- a binary variable.  0=dead at end of survival period,
% 		     1 means still alive 
%    3. age-at-heart-attack -- age in years when heart attack occurred
%    4. pericardial-effusion -- binary. Pericardial effusion is fluid
% 			      around the heart.  0=no fluid, 1=fluid
%    5. fractional-shortening -- a measure of contracility around the heart
% 			       lower numbers are increasingly abnormal
%    6. epss -- E-point septal separation, another measure of contractility.  
% 	      Larger numbers are increasingly abnormal.
%    7. lvdd -- left ventricular end-diastolic dimension.  This is
% 	      a measure of the size of the heart at end-diastole.
% 	      Large hearts tend to be sick hearts.
%    8. wall-motion-score -- a measure of how the segments of the left
% 			   ventricle are moving
%    9. wall-motion-index -- equals wall-motion-score divided by number of
% 			   segments seen.  Usually 12-13 segments are seen
% 			   in an echocardiogram.  Use this variable INSTEAD
% 			   of the wall motion score.
%    10. mult -- a derivate var which can be ignored
%    11. name -- the name of the patient (I have replaced them with "name")
%    12. group -- meaningless, ignore it
%    13. alive-at-1 -- Boolean-valued. Derived from the first two attributes.
%                      0 means patient was either dead after 1 year or had
%                      been followed for less than 1 year.  1 means patient 
%                      was alive at 1 year.
%
% 8. Missing Attribute Values: (denoted by "?")
%    Attribute #:    Number of Missing Values: (total: 132)
%    ------------    -------------------------
%               1    2  
%               2	   1  
%               3	   5  
%               4	   1  
%               5	   8  
%               6	   15 
%               7	   11 
%               8	   4  
%               9	   1  
%              10	   4 
%              11	   0 
%              12	   22
%              13	   58
%
% 9. Distribution of attribute number 2: still-alive
%    Value   Number of instances with this value
%     ----   -----------------------------------
%       0    88 (dead)
%       1    43 (alive)
%       ?    1
%     Total  132
%
%
% 10. Distribution of attribute number 13: alive-at-1
%    Value   Number of instances with this value
%     ----   -----------------------------------
%       0    50
%       1    24
%       ?    58
%     Total  132
%
@RELATION echocardiogram-uci

@ATTRIBUTE survival STRING
@ATTRIBUTE still-alive STRING
@ATTRIBUTE age-at-heart-attack STRING
@ATTRIBUTE pericardial-effusion INTEGER
@ATTRIBUTE fractional-shortening STRING
@ATTRIBUTE epss STRING
@ATTRIBUTE lvdd STRING
@ATTRIBUTE wall-motion-score STRING
@ATTRIBUTE wall-motion-index STRING
@ATTRIBUTE mult STRING
@ATTRIBUTE name STRING
@ATTRIBUTE group STRING
@ATTRIBUTE alive-at-1 STRING

@DATA
11,0,71,0,0.260,9,4.600,14,1,1,name,1,0
19,0,72,0,0.380,6,4.100,14,1.700,0.588,name,1,0
16,0,55,0,0.260,4,3.420,14,1,1,name,1,0
57,0,60,0,0.253,12.062,4.603,16,1.450,0.788,name,1,0
19,1,57,0,0.160,22,5.750,18,2.250,0.571,name,1,0
26,0,68,0,0.260,5,4.310,12,1,0.857,name,1,0
13,0,62,0,0.230,31,5.430,22.5,1.875,0.857,name,1,0
50,0,60,0,0.330,8,5.250,14,1,1,name,1,0
19,0,46,0,0.340,0,5.090,16,1.140,1.003,name,1,0
25,0,54,0,0.140,13,4.490,15.5,1.190,0.930,name,1,0
10,1,77,0,0.130,16,4.230,18,1.800,0.714,name,1,1
52,0,62,1,0.450,9,3.600,16,1.140,1.003,name,1,0
52,0,73,0,0.330,6,4,14,1,1,name,1,0
44,0,60,0,0.150,10,3.730,14,1,1,name,1,0
0.5,1,62,0,0.120,23,5.800,11.67,2.330,0.358,name,1,1
24,0,55,1,0.250,12.063,4.290,14,1,1,name,1,0
0.5,1,69,1,0.260,11,4.650,18,1.640,0.784,name,1,1
0.5,1,62.529,1,0.070,20,5.200,24,2,0.857,name,1,1
22,1,66,0,0.090,17,5.819,8,1.333,0.429,name,1,0
1,1,66,1,0.220,15,5.400,27,2.250,0.857,name,1,1
0.75,1,69,0,0.150,12,5.390,19.5,1.625,0.857,name,1,1
0.75,1,85,1,0.180,19,5.460,13.83,1.380,0.710,name,1,1
0.5,1,73,0,0.230,12.733,6.060,7.5,1.500,0.360,name,1,1
5,1,71,0,0.170,0,4.650,8,1,0.570,name,1,1
48,0,64,0,0.190,5.9,3.480,10,1.110,0.640,name,2,?
29,0,54,0,0.300,7,3.850,10,1.667,0.430,name,2,?
29,0,35,0,0.300,5,4.170,14,1,1,name,2,?
29,0,55,0,?,7,?,2,1,2,name,2,?
0.25,1,75,0,?,?,?,?,1,?,name,2,?
36,0,55,1,0.210,4.2,4.160,14,1.560,0.640,name,2,0
1,1,65,0,0.150,?,5.050,10,1,0.710,name,2,?
1,1,52,1,0.170,17.200,5.320,14,1.170,0.857,name,2,?
03,1,?,0,?,12,?,6,3,0.140,name,2,?
27,0,47,0,0.400,5.120,3.100,12,1,0.857,name,2,?
35,0,63,0,?,10,?,14,1.170,0.857,name,2,0
26,0,61,0,0.610,13.100,4.070,13,1.625,0.571,name,2,0
16,0,63,1,?,?,5.310,5,1,0.357,name,2,0
1,1,65,0,0.060,23.600,?,21.500,2.150,0.714,name,2,1
19,0,68,0,0.510,?,3.880,15,1.670,0.640,name,2,0
31,0,80,0,0.410,5.400,4.360,?,1,?,name,2,?
32,0,54,0,0.350,9.300,3.630,11,1.222,0.640,name,2,0
16,0,70,1,0.270,4.700,4.490,22,2,0.786,name,2,0
40,0,79,0,0.150,17.500,4.270,13,1.300,0.714,name,2,0
46,0,56,0,0.330,?,3.590,14,1,1,name,2,0
2,1,67,1,0.440,9,3.960,17.500,1.450,0.857,name,2,?
37,0,64,0,0.090,?,?,12,2,0.428,name,2,?
19.5,1,81,0,0.120,?,?,9,1.250,0.570,name,2,0
20,1,59,0,0.030,21.300,6.290,17,1.310,0.928,name,2,0
0.25,1,63,1,?,?,?,23,2.300,0.714,name,2,1
?,?,?,77,?,?,?,?,?,2,?,name,2
2,1,56,1,0.040,14,5,?,?,?,name,2,1
7,1,61,1,0.270,?,?,9,1.500,0.428,name,2,1
10,0,57,0,0.240,14.800,5.260,18,1.380,0.812,name,2,?
12,0,58,0,0.300,9.400,3.490,14,1,1,name,2,0
1,1,60,0,0.010,24.600,5.650,39,3,0.928,name,2,1
10,0,66,0,0.290,15.600,6.150,14,1,1,name,2,0
45,0,63,0,0.15,13,4.57,13,1.08,0.857,name,2,0
22,0,57,0,0.13,18.6,4.37,12.33,1.37,0.642,name,2,0
53,0,70,0,0.10,9.8,5.30,23,2.30,0.714,name,2,0
38,0,68,0,0.29,?,4.41,14,1.167,0.857,name,2,?
26,0,79,0,0.17,11.9,5.15,10.5,1.05,0.714,name,2,0
9,0,73,0,0.12,?,6.78,16.67,1.39,0.857,name,2,?
26,0,72,0,0.187,12,5.02,13,1.18,0.785,name,2,0
0.5,1,59,0,0.13,16.4,4.96,17.83,1.37,0.928,name,2,?
12,0,67,1,0.11,10.3,4.68,11,1,0.785,name,2,?
49,0,51,0,0.16,13.2,5.26,11,1,0.786,name,2,0
0.75,1,50,0,0.14,11.4,4.75,10,2.5,0.28,name,2,?
49,0,70,1,0.25,9.7,5.57,5.5,1.10,0.357,name,2,0
47,0,65,0,0.36,8.8,5.78,12,1,0.857,name,2,0
41,0,78,0,0.06,16.1,5.62,13.67,1.367,0.714,name,2,0
.25,1,86,0,0.225,12.2,5.20,24,2.18,0.786,name,2,1
33,0,56,0,0.25,11,4.72,11,1,0.785,name,2,0
29,0,60,0,0.12,10.2,4.31,15,1.67,0.64,name,2,0
41,0,59,0,0.29,7.5,4.75,13,1.08,0.857,name,2,0
26,0,50,0,0.06,30.1,5.95,21.5,2.39,0.643,name,2,?
15,0,54,0,0.217,17.9,4.54,16.5,1.18,1,name,2,0
.25,1,68,0,0.22,21.7,4.85,15,1.15,0.928,name,2,?
.03,1,?,0,0.26,19.4,4.77,21,2.1,0.714,name,2,1
12,0,64,0,0.20,7.1,4.58,14,1,1,name,2,0
32,0,63,0,0.20,5,5.20,8,1,0.57,name,2,?
32,0,65,0,0.06,23.6,6.74,12,1.09,0.785,name,2,?
27,0,54,1,0.07,16.8,4.16,18,1.5,0.857,name,2,0
23,0,62,0,0.25,6,4.48,11,1,0.786,name,2,?
0.75,1,78,0,0.05,10,4.44,15,1.36,0.786,name,2,1
0.75,1,61,0,?,?,?,28,2.33,0.857,name,2,1
34,0,52,0,0.14,25,6.21,11.5,1.15,0.714,name,2,?
1,1,73,0,0.05,14.8,4.14,15.5,1.41,0.786,name,2,?
21,1,70,1,0.16,19.2,5.25,11,1,0.786,name,2,?
55,0,55,0,0.28,5.5,4.48,22,1.83,0.857,name,2,0
15,1,60,0,0.18,8.7,4.56,13.5,1.04,0.928,name,2,?
0.5,1,67,0,0.155,11.3,5.16,13,1,0.928,name,2,?
35,0,64,0,0.30,6.6,4.36,14,1.27,0.786,name,2,?
53,0,59,0,0.344,9.1,4.04,9,1,0.643,name,2,0
33,0,46,0,0.272,16.5,5.36,12.67,1.06,0.857,name,2,?
?,1,61,0,0.20,9.4,4.02,15.67,1.42,0.786,name,2,1
33,0,63,0,0.25,5.6,3.87,18,1.50,0.857,name,2,?
40,1,74,0,0.20,4.8,4.56,12.5,1.04,0.857,name,2,0
33,0,59,0,0.50,9.1,3.42,18,1.5,0.857,name,2,?
5,1,65,1,0.16,8.5,5.47,16,1.45,0.786,name,2,1
4,1,58,0,0.17,28.9,6.73,26.08,2.01,0.928,name,2,1
31,0,53,0,0.17,?,4.69,10,1,0.71,name,2,?
33,0,66,0,0.20,?,4.23,12,1,0.857,name,2,0
22,0,70,0,0.38,0,4.55,10,1,0.714,name,2,0
25,0,62,0,0.258,11.8,4.87,11,1,0.786,name,2,?
1.25,1,63,0,0.30,6.9,3.52,18.16,1.51,0.857,name,2,1
24,0,59,0,0.17,14.3,5.49,13.5,1.50,0.643,name,2,0
25,0,57,0,0.228,9.7,4.29,11,1,0.786,name,2,0
24,0,57,0,0.036,7,4.12,13.5,1.23,0.786,name,2,?
.75,1,78,0,0.23,40,6.23,14,1.4,0.714,name,2,1
3,1,62,0,0.26,7.6,4.42,14,1,1,name,2,1
27,0,62,0,0.22,12.1,3.92,11,1,0.785,name,?,?
13,0,66,0,0.24,13.6,4.38,22,2.20,0.714,name,?,?
36,0,61,0,0.27,9.00,4.06,12,1,0.857,name,?,?
25,0,59,1,0.40,9.20,5.36,12,1,0.857,name,?,?
27,0,57,0,0.29,9.40,4.77,9,1,0.64,name,?,?
34,0,62,1,0.19,28.9,6.63,19.5,1.95,0.714,name,?,?
37,0,?,0,0.26,0,4.38,9,1,0.64,name,?,?
34,0,54,0,0.43,9.30,4.79,10,1,0.714,name,?,?
28,1,62,1,0.24,28.6,5.86,21.5,1.95,0.786,name,?,?
28,0,?,0,0.23,19.1,5.49,12,1.20,0.71,name,?,?
17,0,64,0,0.15,6.60,4.17,14,1.27,0.786,name,?,?
38,0,57,1,0.12,0,2.32,16.5,1.375,0.857,name,?,?
31,0,61,0,0.18,0,4.48,11,1.375,0.57,name,?,?
12,0,61,1,0.19,13.2,5.04,19,1.73,0.786,name,?,?
36,0,48,0,0.15,12,3.66,10,1,0.714,name,?,?
17,0,?,0,0.09,6.80,4.96,13,1.08,0.857,name,?,?
21,0,61,0,0.14,25.5,5.16,14,1.27,0.786,name,?,?
7.5,1,64,0,0.24,12.9,4.72,12,1,0.857,name,?,?
41,0,64,0,0.28,5.40,5.47,11,1.10,0.714,name,?,?
36,0,69,0,0.20,7.00,5.05,14.5,1.21,0.857,name,?,?
22,0,57,0,0.14,16.1,4.36,15,1.36,0.786,name,?,?
20,0,62,0,0.15,0,4.51,15.5,1.409,0.786,name,?,?