Data
wdbc

wdbc

active ARFF Publicly available Visibility: public Uploaded 26-05-2015 by Rafael Gomes Mantovani
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31 features

Class (target)nominal2 unique values
0 missing
V1numeric456 unique values
0 missing
V2numeric479 unique values
0 missing
V3numeric522 unique values
0 missing
V4numeric539 unique values
0 missing
V5numeric474 unique values
0 missing
V6numeric537 unique values
0 missing
V7numeric537 unique values
0 missing
V8numeric542 unique values
0 missing
V9numeric432 unique values
0 missing
V10numeric499 unique values
0 missing
V11numeric540 unique values
0 missing
V12numeric519 unique values
0 missing
V13numeric533 unique values
0 missing
V14numeric528 unique values
0 missing
V15numeric547 unique values
0 missing
V16numeric541 unique values
0 missing
V17numeric533 unique values
0 missing
V18numeric507 unique values
0 missing
V19numeric498 unique values
0 missing
V20numeric545 unique values
0 missing
V21numeric457 unique values
0 missing
V22numeric511 unique values
0 missing
V23numeric514 unique values
0 missing
V24numeric544 unique values
0 missing
V25numeric411 unique values
0 missing
V26numeric529 unique values
0 missing
V27numeric539 unique values
0 missing
V28numeric492 unique values
0 missing
V29numeric500 unique values
0 missing
V30numeric535 unique values
0 missing

107 properties

569
Number of instances (rows) of the dataset.
31
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.
30
Number of numeric attributes.
1
Number of nominal attributes.
0.06
First quartile of means among attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.06
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
0.06
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of mutual information between the nominal attributes and the target attribute.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.87
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
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
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.
0.98
First quartile of skewness among attributes of the numeric type.
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.96
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.
0.06
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
0.02
First quartile of standard deviation of attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.06
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
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
1.74
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.87
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
0.04
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
62.74
Percentage of instances belonging to the most frequent class.
34.9
Mean standard deviation of attributes of the numeric type.
3.02
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.95
Entropy of the target attribute values.
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
357
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.22
Second quartile (Median) of means among attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.87
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.54
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.09
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
49.21
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
1.42
Second quartile (Median) of skewness among attributes of the numeric type.
0.89
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.8
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
880.58
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
3.23
Percentage of binary attributes.
0.07
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.05
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.06
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.
0.42
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
5.99
Third quartile of kurtosis among attributes of the numeric type.
0.63
Average class difference between consecutive instances.
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
5.45
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
96.77
Percentage of numeric attributes.
17.02
Third quartile of means among attributes of the numeric type.
0.96
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
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.06
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
569.36
Maximum standard deviation of attributes of the numeric type.
37.26
Percentage of instances belonging to the least frequent class.
3.23
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.06
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
0.06
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
212
Number of instances belonging to the least frequent class.
First quartile of entropy among attributes.
1.98
Third quartile of skewness among attributes of the numeric type.
0.87
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
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
7.81
Mean kurtosis among attributes of the numeric type.
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.97
First quartile of kurtosis among attributes of the numeric type.
4.43
Third quartile of standard deviation of attributes of the numeric type.
0.96
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
0.93
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.06
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
61.89
Mean of means among attributes of the numeric type.
0.07
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes

11 tasks

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 10% Holdout set - target_feature: Class
0 runs - estimation_procedure: Test on Training Data - target_feature: Class
0 runs - estimation_procedure: Leave one out - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - target_feature: Class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
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