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sa-heart

sa-heart

active ARFF Publicly available Visibility: public Uploaded 25-05-2015 by Rafael Gomes Mantovani
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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

107 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
Maximum entropy among attributes.
-1.02
Minimum kurtosis among attributes of the numeric type.
25.73
Second quartile (Median) of means among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
6.42
Maximum kurtosis among attributes of the numeric type.
3.64
Minimum of means among attributes of the numeric type.
0.05
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.31
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.35
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
138.33
Maximum of means among attributes of the numeric type.
0.05
Minimal mutual information between the nominal attributes and the target attribute.
1.04
Second quartile (Median) of skewness among attributes of the numeric type.
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
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.
20
Percentage of binary attributes.
8.8
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.02
Number of attributes divided by the number of instances.
2
The maximum number of distinct values among attributes of the nominal type.
-0.38
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
0.98
Third quartile of entropy among attributes.
0.41
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
17.42
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
2.31
Maximum skewness among attributes of the numeric type.
2.07
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
5.2
Third quartile of kurtosis among attributes of the numeric type.
0.56
Average class difference between consecutive instances.
0.08
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
24.48
Maximum standard deviation of attributes of the numeric type.
34.63
Percentage of instances belonging to the least frequent class.
80
Percentage of numeric attributes.
50.53
Third quartile of means among attributes of the numeric type.
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.32
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.98
Average entropy of the attributes.
160
Number of instances belonging to the least frequent class.
20
Percentage of nominal attributes.
0.05
Third quartile of mutual information between the nominal attributes and the target attribute.
0.28
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.41
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.26
Mean kurtosis among attributes of the numeric type.
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.98
First quartile of entropy among attributes.
1.89
Third quartile of skewness among attributes of the numeric type.
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.08
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
38.89
Mean of means among attributes of the numeric type.
0.29
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.41
First quartile of kurtosis among attributes of the numeric type.
19.02
Third quartile of standard deviation of attributes of the numeric type.
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.54
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.32
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.05
Average mutual information between the nominal attributes and the target attribute.
0.37
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
7.82
First quartile of means among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.28
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.41
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
17.33
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2
Number of binary attributes.
0.05
First quartile of mutual information between the nominal attributes and the target attribute.
0.31
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.08
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
-0.31
First quartile of skewness among attributes of the numeric type.
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.32
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.86
Mean skewness among attributes of the numeric type.
4.31
First quartile of standard deviation of attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.28
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
11.01
Mean standard deviation of attributes of the numeric type.
0.98
Second quartile (Median) of entropy among attributes.
0.31
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
0.36
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
65.37
Percentage of instances belonging to the most frequent class.
302
Number of instances belonging to the most frequent class.
0.98
Minimal entropy among attributes.
2.02
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.93
Entropy of the target attribute values.
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk

14 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
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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