Data
BNG(breast-w)

BNG(breast-w)

active ARFF Publicly available Visibility: public Uploaded 28-04-2014 by Jan van Rijn
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10 features

Class (target)nominal2 unique values
0 missing
Clump_Thicknessnumeric26387 unique values
0 missing
Cell_Size_Uniformitynumeric17780 unique values
0 missing
Cell_Shape_Uniformitynumeric16030 unique values
0 missing
Marginal_Adhesionnumeric13232 unique values
0 missing
Single_Epi_Cell_Sizenumeric10910 unique values
0 missing
Bare_Nucleinumeric8561 unique values
0 missing
Bland_Chromatinnumeric11991 unique values
0 missing
Normal_Nucleolinumeric11095 unique values
0 missing
Mitosesnumeric2988 unique values
0 missing

107 properties

39366
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.
9
Number of numeric attributes.
1
Number of nominal attributes.
3.62
Maximum standard deviation of attributes of the numeric type.
34.41
Percentage of instances belonging to the least frequent class.
90
Percentage of numeric attributes.
3.45
Third quartile of means among attributes of the numeric type.
0.98
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
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
13546
Number of instances belonging to the least frequent class.
10
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.02
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
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.64
Mean kurtosis among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
1.6
Third quartile of skewness among attributes of the numeric type.
0.95
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
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
3.13
Mean of means among attributes of the numeric type.
0.04
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.27
First quartile of kurtosis among attributes of the numeric type.
3.05
Third quartile of standard deviation of attributes of the numeric type.
0.98
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
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.9
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.86
First quartile of means among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.02
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
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.95
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
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.98
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.
1.06
First quartile of skewness among attributes of the numeric type.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.98
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.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
1.47
Mean skewness among attributes of the numeric type.
2.32
First quartile of standard deviation of attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.02
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
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.75
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.95
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
0.02
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
65.59
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.12
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.93
Entropy of the target attribute values.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
25820
Number of instances belonging to the most frequent class.
-0.73
Minimum kurtosis among attributes of the numeric type.
3.2
Second quartile (Median) of means among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.9
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
1.59
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.08
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
12.39
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
1.24
Second quartile (Median) of skewness among attributes of the numeric type.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.82
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
4.39
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
10
Percentage of binary attributes.
2.87
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
0.6
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
2
The maximum number of distinct values among attributes of the nominal type.
1.71
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
1.49
Third quartile of kurtosis among attributes of the numeric type.
0.55
Average class difference between consecutive instances.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.52
Maximum skewness among attributes of the numeric type.

17 tasks

354 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
225 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
190 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
73 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Class
25 runs - estimation_procedure: Interleaved Test then Train - 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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