heart-c.arff

是UCI数据库中的一些有代表性的数据集

% Publication Request: 
%    >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
%    This file describes the contents of the heart-disease directory.
% 
%    This directory contains 4 databases concerning heart disease diagnosis.
%    All attributes are numeric-valued.  The data was collected from the
%    four following locations:
% 
%      1. Cleveland Clinic Foundation (cleveland.data)
%      2. Hungarian Institute of Cardiology, Budapest (hungarian.data)
%      3. V.A. Medical Center, Long Beach, CA (long-beach-va.data)
%      4. University Hospital, Zurich, Switzerland (switzerland.data)
% 
%    Each database has the same instance format.  While the databases have 76
%    raw attributes, only 14 of them are actually used.  Thus I've taken the
%    liberty of making 2 copies of each database: one with all the attributes
%    and 1 with the 14 attributes actually used in past experiments.
% 
%    The authors of the databases have requested:
% 
%       ...that any publications resulting from the use of the data include the 
%       names of the principal investigator responsible for the data collection
%       at each institution.  They would be:
% 
%        1. Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D.
%        2. University Hospital, Zurich, Switzerland: William Steinbrunn, M.D.
%        3. University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D.
%        4. V.A. Medical Center, Long Beach and Cleveland Clinic Foundation:
%           Robert Detrano, M.D., Ph.D.
% 
%    Thanks in advance for abiding by this request.
% 
%    David Aha
%    July 22, 1988
%    >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
% 
% 1. Title: Heart Disease Databases
% 
% 2. Source Information:
%    (a) Creators: 
%        -- 1. Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D.
%        -- 2. University Hospital, Zurich, Switzerland: William Steinbrunn, M.D.
%        -- 3. University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D.
%        -- 4. V.A. Medical Center, Long Beach and Cleveland Clinic Foundation:
%              Robert Detrano, M.D., Ph.D.
%    (b) Donor: David W. Aha ([e-mail]) [phone]   
%    (c) Date: July, 1988
% 
% 3. Past Usage:
%     1. Detrano,~R., Janosi,~A., Steinbrunn,~W., Pfisterer,~M., Schmid,~J.,
%        Sandhu,~S., Guppy,~K., Lee,~S., \& Froelicher,~V. (1989).  {\it 
%        International application of a new probability algorithm for the 
%        diagnosis of coronary artery disease.}  {\it American Journal of 
%        Cardiology}, {\it 64},304--310.
%        -- International Probability Analysis 
%        -- Address: Robert Detrano, M.D.
%                    Cardiology 111-C
%                    V.A. Medical Center
%                    5901 E. 7th Street
%                    Long Beach, CA 90028
%        -- Results in percent accuracy: (for 0.5 probability threshold)
%              Data Name:  CDF    CADENZA
%           -- Hungarian   77     74
%              Long beach  79     77
%              Swiss       81     81
%           -- Approximately a 77% correct classification accuracy with a
%              logistic-regression-derived discriminant function
%     2. David W. Aha & Dennis Kibler
%        -- 
%           
%           
%           -- Instance-based prediction of heart-disease presence with the 
%              Cleveland database
%              -- NTgrowth: 77.0% accuracy
%              --       C4: 74.8% accuracy
%     3. John Gennari
%        -- Gennari, J.~H., Langley, P, \& Fisher, D. (1989). Models of
%           incremental concept formation. {\it Artificial Intelligence, 40},
%           11--61.
%        -- Results: 
%           -- The CLASSIT conceptual clustering system achieved a 78.9% accuracy
%              on the Cleveland database.
% 
% 4. Relevant Information:
%      This database contains 76 attributes, but all published experiments
%      refer to using a subset of 14 of them.  In particular, the Cleveland
%      database is the only one that has been used by ML researchers to 
%      this date.  The "goal" field refers to the presence of heart disease
%      in the patient.  It is integer valued from 0 (no presence) to 4.
%      Experiments with the Cleveland database have concentrated on simply
%      attempting to distinguish presence (values 1,2,3,4) from absence (value
%      0).  
%    
%      The names and social security numbers of the patients were recently 
%      removed from the database, replaced with dummy values.
% 
%      One file has been "processed", that one containing the Cleveland 
%      database.  All four unprocessed files also exist in this directory.
%     
% 5. Number of Instances: 
%         Database:    # of instances:
%           Cleveland: 303
%           Hungarian: 294
%         Switzerland: 123
%       Long Beach VA: 200
% 
% 6. Number of Attributes: 76 (including the predicted attribute)
% 
% 7. Attribute Information:
%    -- Only 14 used
%       -- 1. #3  (age)       
%       -- 2. #4  (sex)       
%       -- 3. #9  (cp)        
%       -- 4. #10 (trestbps)  
%       -- 5. #12 (chol)      
%       -- 6. #16 (fbs)       
%       -- 7. #19 (restecg)   
%       -- 8. #32 (thalach)   
%       -- 9. #38 (exang)     
%       -- 10. #40 (oldpeak)   
%       -- 11. #41 (slope)     
%       -- 12. #44 (ca)        
%       -- 13. #51 (thal)      
%       -- 14. #58 (num)       (the predicted attribute)
% 
%    -- Complete attribute documentation:
%       1 id: patient identification number
%       2 ccf: social security number (I replaced this with a dummy value of 0)
%       3 age: age in years
%       4 sex: sex (1 = male; 0 = female)
%       5 painloc: chest pain location (1 = substernal; 0 = otherwise)
%       6 painexer (1 = provoked by exertion; 0 = otherwise)
%       7 relrest (1 = relieved after rest; 0 = otherwise)
%       8 pncaden (sum of 5, 6, and 7)
%       9 cp: chest pain type
%         -- Value 1: typical angina
%         -- Value 2: atypical angina
%         -- Value 3: non-anginal pain
%         -- Value 4: asymptomatic
%      10 trestbps: resting blood pressure (in mm Hg on admission to the 
%         hospital)
%      11 htn
%      12 chol: serum cholestoral in mg/dl
%      13 smoke: I believe this is 1 = yes; 0 = no (is or is not a smoker)
%      14 cigs (cigarettes per day)
%      15 years (number of years as a smoker)
%      16 fbs: (fasting blood sugar > 120 mg/dl)  (1 = true; 0 = false)
%      17 dm (1 = history of diabetes; 0 = no such history)
%      18 famhist: family history of coronary artery disease (1 = yes; 0 = no)
%      19 restecg: resting electrocardiographic results
%         -- Value 0: normal
%         -- Value 1: having ST-T wave abnormality (T wave inversions and/or ST 
%                     elevation or depression of > 0.05 mV)
%         -- Value 2: showing probable or definite left ventricular hypertrophy
%                     by Estes' criteria
%      20 ekgmo (month of exercise ECG reading)
%      21 ekgday(day of exercise ECG reading)
%      22 ekgyr (year of exercise ECG reading)
%      23 dig (digitalis used furing exercise ECG: 1 = yes; 0 = no)
%      24 prop (Beta blocker used during exercise ECG: 1 = yes; 0 = no)
%      25 nitr (nitrates used during exercise ECG: 1 = yes; 0 = no)
%      26 pro (calcium channel blocker used during exercise ECG: 1 = yes; 0 = no)
%      27 diuretic (diuretic used used during exercise ECG: 1 = yes; 0 = no)
%      28 proto: exercise protocol
%           1 = Bruce     
%           2 = Kottus
%           3 = McHenry
%           4 = fast Balke
%           5 = Balke
%           6 = Noughton 
%           7 = bike 150 kpa min/min  (Not sure if "kpa min/min" is what was 
%               written!)
%           8 = bike 125 kpa min/min  
%           9 = bike 100 kpa min/min
%          10 = bike 75 kpa min/min
%          11 = bike 50 kpa min/min
%          12 = arm ergometer
%      29 thaldur: duration of exercise test in minutes
%      30 thaltime: time when ST measure depression was noted
%      31 met: mets achieved
%      32 thalach: maximum heart rate achieved
%      33 thalrest: resting heart rate
%      34 tpeakbps: peak exercise blood pressure (first of 2 parts)
%      35 tpeakbpd: peak exercise blood pressure (second of 2 parts)
%      36 dummy
%      37 trestbpd: resting blood pressure
%      38 exang: exercise induced angina (1 = yes; 0 = no)
%      39 xhypo: (1 = yes; 0 = no)
%      40 oldpeak = ST depression induced by exercise relative to rest
%      41 slope: the slope of the peak exercise ST segment
%         -- Value 1: upsloping
%         -- Value 2: flat
%         -- Value 3: downsloping
%      42 rldv5: height at rest
%      43 rldv5e: height at peak exercise
%      44 ca: number of major vessels (0-3) colored by flourosopy
%      45 restckm: irrelevant
%      46 exerckm: irrelevant
%      47 restef: rest raidonuclid (sp?) ejection fraction
%      48 restwm: rest wall (sp?) motion abnormality
%         0 = none
%         1 = mild or moderate
%         2 = moderate or severe
%         3 = akinesis or dyskmem (sp?)
%      49 exeref: exercise radinalid (sp?) ejection fraction
%      50 exerwm: exercise wall (sp?) motion