Data

mammography

active ARFF Publicly available Visibility: public Uploaded 25-08-2014 by Tobias Kuehn
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  • mythbusting_1 study_1 study_15 study_20 study_50 study_7
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Author: Source: Unknown - Please cite: Mammography dataset Past Usage: 1. Woods, K., Doss, C., Bowyer, K., Solka, J., Priebe, C.,

7 features

class (target)nominal2 unique values
0 missing
attr1numeric5435 unique values
0 missing
attr2numeric883 unique values
0 missing
attr3numeric160 unique values
0 missing
attr4numeric2800 unique values
0 missing
attr5numeric1739 unique values
0 missing
attr6numeric550 unique values
0 missing

106 properties

11183
Number of instances (rows) of the dataset.
7
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.
6
Number of numeric attributes.
1
Number of nominal attributes.
0.8
Second quartile (Median) of means among attributes of the numeric type.
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
10923
Number of instances belonging to the most frequent class.
-1.81
Minimum kurtosis among attributes of the numeric type.
NaN
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
0.02
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
NaN
Maximum entropy among attributes.
-29
Minimum of means among attributes of the numeric type.
0.78
Second quartile (Median) of skewness among attributes of the numeric type.
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
163.26
Maximum kurtosis among attributes of the numeric type.
NaN
Minimal mutual information between the nominal attributes and the target attribute.
14.29
Percentage of binary attributes.
1.39
DataQuality extracted from Fantail Library
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.98
The predictive accuracy obtained by always predicting the majority class.
1409.62
Maximum of means among attributes of the numeric type.
-1
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of instances having missing values.
NaN
Third quartile of entropy among attributes.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.
NaN
Maximum mutual information between the nominal attributes and the target attribute.
-5.71
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
13.87
Third quartile of kurtosis among attributes of the numeric type.
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
NaN
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
-1
The maximum number of distinct values among attributes of the nominal type.
0
DataQuality extracted from Fantail Library
85.71
Percentage of numeric attributes.
26.45
Third quartile of means among attributes of the numeric type.
0.84
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
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
8.89
Maximum skewness among attributes of the numeric type.
260
Number of instances belonging to the least frequent class.
14.29
Percentage of nominal attributes.
NaN
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
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
11382.8
DataQuality extracted from Fantail Library
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaN
First quartile of entropy among attributes.
2.9
DataQuality extracted from Fantail Library
0.54
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
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
-1
Average entropy of the attributes.
0.04
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.43
First quartile of kurtosis among attributes of the numeric type.
20.23
DataQuality extracted from Fantail Library
0.84
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
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
14.63
Mean kurtosis among attributes of the numeric type.
0.41
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.4
First quartile of means among attributes of the numeric type.
0.85
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
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
65.43
Mean of means among attributes of the numeric type.
NaN
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NaN
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
0.54
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
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
NaN
Average mutual information between the nominal attributes and the target attribute.
1
Number of binary attributes.
0
First quartile of skewness among attributes of the numeric type.
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.84
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
-1
Standard deviation of the number of distinct values among attributes of the nominal type.
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
-1
Average number of distinct values among the attributes of the nominal type.
0.24
DataQuality extracted from Fantail Library
0.85
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
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
1.83
Mean skewness among attributes of the numeric type.
NaN
Second quartile (Median) of entropy among attributes.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.54
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
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
312.47
Mean standard deviation of attributes of the numeric type.
0.69
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.16
Entropy of the target attribute values.
0.6
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
97.68
Percentage of instances belonging to the most frequent class.
NaN
Minimal entropy among attributes.

8 tasks

151 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
Define a new task

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