Data
sa-heart

sa-heart

active ARFF Publicly available Visibility: public Uploaded 25-05-2015 by Rafael G. Mantovani
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  • mf_less_than_80 study_123 study_50 study_52 study_7 study_88
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Author: Source: http://statweb.stanford.edu/~tibs/ElemStatLearn/data.html Please cite: * Title: South Africa Heart Disease Dataset * Description A retrospective sample of males in a heart-disease high-risk region of the Western Cape, South Africa. There are roughly two controls per case of CHD. Many of the CHD positive men have undergone blood pressure reduction treatment and other programs to reduce their risk factors after their CHD event. In some cases the measurements were made after these treatments. These data are taken from a larger dataset, described in Rousseauw et al, 1983, South African Medical Journal. * Attributes: sbp systolic blood pressure tobacco cumulative tobacco (kg) ldl low densiity lipoprotein cholesterol adiposity famhist family history of heart disease (Present, Absent) typea type-A behavior obesity alcohol current alcohol consumption age age at onset chd response, coronary heart disease

10 features

Class (target)nominal2 unique values
0 missing
V1numeric62 unique values
0 missing
V2numeric214 unique values
0 missing
V3numeric329 unique values
0 missing
V4numeric408 unique values
0 missing
V5nominal2 unique values
0 missing
V6numeric54 unique values
0 missing
V7numeric400 unique values
0 missing
V8numeric249 unique values
0 missing
V9numeric49 unique values
0 missing

62 properties

462
Number of instances (rows) of the dataset.
10
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
8
Number of numeric attributes.
2
Number of nominal attributes.
0.98
Second quartile (Median) of entropy among attributes.
0.93
Entropy of the target attribute values.
17.33
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2.02
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.02
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
25.73
Second quartile (Median) of means among attributes of the numeric type.
17.42
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
0.86
Mean skewness among attributes of the numeric type.
0.05
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
65.37
Percentage of instances belonging to the most frequent class.
11.01
Mean standard deviation of attributes of the numeric type.
1.04
Second quartile (Median) of skewness among attributes of the numeric type.
302
Number of instances belonging to the most frequent class.
0.98
Minimal entropy among attributes.
8.8
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.98
Maximum entropy among attributes.
-1.02
Minimum kurtosis among attributes of the numeric type.
20
Percentage of binary attributes.
0.98
Third quartile of entropy among attributes.
6.42
Maximum kurtosis among attributes of the numeric type.
3.64
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
5.2
Third quartile of kurtosis among attributes of the numeric type.
138.33
Maximum of means among attributes of the numeric type.
0.05
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
50.53
Third quartile of means among attributes of the numeric type.
0.05
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
80
Percentage of numeric attributes.
0.05
Third quartile of mutual information between the nominal attributes and the target attribute.
2
The maximum number of distinct values among attributes of the nominal type.
-0.38
Minimum skewness among attributes of the numeric type.
20
Percentage of nominal attributes.
1.89
Third quartile of skewness among attributes of the numeric type.
2.31
Maximum skewness among attributes of the numeric type.
2.07
Minimum standard deviation of attributes of the numeric type.
0.98
First quartile of entropy among attributes.
19.02
Third quartile of standard deviation of attributes of the numeric type.
24.48
Maximum standard deviation of attributes of the numeric type.
34.63
Percentage of instances belonging to the least frequent class.
-0.41
First quartile of kurtosis among attributes of the numeric type.
7.82
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.98
Average entropy of the attributes.
160
Number of instances belonging to the least frequent class.
0.05
First quartile of mutual information between the nominal attributes and the target attribute.
2.26
Mean kurtosis among attributes of the numeric type.
2
Number of binary attributes.
-0.31
First quartile of skewness among attributes of the numeric type.
38.89
Mean of means among attributes of the numeric type.
4.31
First quartile of standard deviation of attributes of the numeric type.
0.56
Average class difference between consecutive instances.
0.05
Average mutual information between the nominal attributes and the target attribute.

6 tasks

124 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
31 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - target_feature: Class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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