Data
BNG(mfeat-zernike)

BNG(mfeat-zernike)

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

class (target)nominal10 unique values
0 missing
att1numeric230641 unique values
0 missing
att2numeric859216 unique values
0 missing
att3numeric986732 unique values
0 missing
att4numeric995744 unique values
0 missing
att5numeric997187 unique values
0 missing
att6numeric998878 unique values
0 missing
att7numeric998379 unique values
0 missing
att8numeric286151 unique values
0 missing
att9numeric902315 unique values
0 missing
att10numeric988649 unique values
0 missing
att11numeric996923 unique values
0 missing
att12numeric997677 unique values
0 missing
att13numeric997844 unique values
0 missing
att14numeric399298 unique values
0 missing
att15numeric955856 unique values
0 missing
att16numeric992472 unique values
0 missing
att17numeric997000 unique values
0 missing
att18numeric997854 unique values
0 missing
att19numeric997985 unique values
0 missing
att20numeric517062 unique values
0 missing
att21numeric964802 unique values
0 missing
att22numeric994950 unique values
0 missing
att23numeric997189 unique values
0 missing
att24numeric997648 unique values
0 missing
att25numeric743330 unique values
0 missing
att26numeric978984 unique values
0 missing
att27numeric995783 unique values
0 missing
att28numeric998028 unique values
0 missing
att29numeric998178 unique values
0 missing
att30numeric801041 unique values
0 missing
att31numeric986644 unique values
0 missing
att32numeric996029 unique values
0 missing
att33numeric997638 unique values
0 missing
att34numeric888641 unique values
0 missing
att35numeric989961 unique values
0 missing
att36numeric997505 unique values
0 missing
att37numeric997830 unique values
0 missing
att38numeric931756 unique values
0 missing
att39numeric992217 unique values
0 missing
att40numeric997653 unique values
0 missing
att41numeric950599 unique values
0 missing
att42numeric996106 unique values
0 missing
att43numeric998362 unique values
0 missing
att44numeric967216 unique values
0 missing
att45numeric996999 unique values
0 missing
att46numeric986226 unique values
0 missing
att47numeric997869 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
48
Number of attributes (columns) of the dataset.
10
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.
47
Number of numeric attributes.
1
Number of nominal attributes.
0.74
Second quartile (Median) of skewness among attributes of the numeric type.
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
507.71
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
37.1
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.81
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.
10
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.
0.35
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.
10
The maximum number of distinct values among attributes of the nominal type.
0.02
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
1.12
Third quartile of kurtosis among attributes of the numeric type.
0.1
Average class difference between consecutive instances.
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.5
Maximum skewness among attributes of the numeric type.
0.07
Minimum standard deviation of attributes of the numeric type.
97.92
Percentage of numeric attributes.
126.53
Third quartile of means among attributes of the numeric type.
0.85
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
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
124.19
Maximum standard deviation of attributes of the numeric type.
9.98
Percentage of instances belonging to the least frequent class.
2.08
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.29
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
0.35
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
99797
Number of instances belonging to the least frequent class.
First quartile of entropy among attributes.
1.13
Third quartile of skewness among attributes of the numeric type.
0.68
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
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.29
Mean kurtosis among attributes of the numeric type.
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.56
First quartile of kurtosis among attributes of the numeric type.
64.83
Third quartile of standard deviation of attributes of the numeric type.
0.85
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
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
88.12
Mean of means among attributes of the numeric type.
0.31
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
7.32
First quartile of means among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.29
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
0.35
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of mutual information between the nominal attributes and the target attribute.
0.27
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.68
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
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.85
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.
0
Number of binary attributes.
0.38
First quartile of skewness among attributes of the numeric type.
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.85
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.
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
10
Average number of distinct values among the attributes of the nominal type.
3.52
First quartile of standard deviation of attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.29
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
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.75
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.27
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.68
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
0.27
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
10.03
Percentage of instances belonging to the most frequent class.
39.71
Mean standard deviation of attributes of the numeric type.
0.02
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.32
Entropy of the target attribute values.
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
100289
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
68.78
Second quartile (Median) of means among attributes of the numeric type.
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.98
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.27
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.81
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
2.23
Maximum kurtosis among attributes of the numeric type.
0.08
Minimum of means among attributes of the numeric type.

25 tasks

6 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 - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
46 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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