Data
BNG(mfeat-fourier)

BNG(mfeat-fourier)

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

class (target)nominal10 unique values
0 missing
att1numeric319707 unique values
0 missing
att2numeric494126 unique values
0 missing
att3numeric425464 unique values
0 missing
att4numeric375893 unique values
0 missing
att5numeric469621 unique values
0 missing
att6numeric324200 unique values
0 missing
att7numeric452032 unique values
0 missing
att8numeric398580 unique values
0 missing
att9numeric400491 unique values
0 missing
att10numeric312082 unique values
0 missing
att11numeric314010 unique values
0 missing
att12numeric310367 unique values
0 missing
att13numeric328137 unique values
0 missing
att14numeric367135 unique values
0 missing
att15numeric255448 unique values
0 missing
att16numeric239552 unique values
0 missing
att17numeric260758 unique values
0 missing
att18numeric288843 unique values
0 missing
att19numeric253740 unique values
0 missing
att20numeric221767 unique values
0 missing
att21numeric218016 unique values
0 missing
att22numeric218866 unique values
0 missing
att23numeric228813 unique values
0 missing
att24numeric250551 unique values
0 missing
att25numeric203136 unique values
0 missing
att26numeric209969 unique values
0 missing
att27numeric201056 unique values
0 missing
att28numeric206614 unique values
0 missing
att29numeric212122 unique values
0 missing
att30numeric193296 unique values
0 missing
att31numeric191646 unique values
0 missing
att32numeric187254 unique values
0 missing
att33numeric194644 unique values
0 missing
att34numeric189748 unique values
0 missing
att35numeric185514 unique values
0 missing
att36numeric184187 unique values
0 missing
att37numeric177583 unique values
0 missing
att38numeric178651 unique values
0 missing
att39numeric179621 unique values
0 missing
att40numeric177791 unique values
0 missing
att41numeric173318 unique values
0 missing
att42numeric169282 unique values
0 missing
att43numeric168905 unique values
0 missing
att44numeric170531 unique values
0 missing
att45numeric174427 unique values
0 missing
att46numeric165557 unique values
0 missing
att47numeric168862 unique values
0 missing
att48numeric165831 unique values
0 missing
att49numeric179611 unique values
0 missing
att50numeric178106 unique values
0 missing
att51numeric179206 unique values
0 missing
att52numeric180947 unique values
0 missing
att53numeric188445 unique values
0 missing
att54numeric190434 unique values
0 missing
att55numeric196154 unique values
0 missing
att56numeric185558 unique values
0 missing
att57numeric208907 unique values
0 missing
att58numeric208780 unique values
0 missing
att59numeric200160 unique values
0 missing
att60numeric215442 unique values
0 missing
att61numeric235840 unique values
0 missing
att62numeric220073 unique values
0 missing
att63numeric237663 unique values
0 missing
att64numeric227552 unique values
0 missing
att65numeric248852 unique values
0 missing
att66numeric264062 unique values
0 missing
att67numeric263900 unique values
0 missing
att68numeric257908 unique values
0 missing
att69numeric323549 unique values
0 missing
att70numeric322070 unique values
0 missing
att71numeric316815 unique values
0 missing
att72numeric322101 unique values
0 missing
att73numeric403137 unique values
0 missing
att74numeric414668 unique values
0 missing
att75numeric307418 unique values
0 missing
att76numeric394636 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
77
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.
76
Number of numeric attributes.
1
Number of nominal attributes.
0.67
Third quartile of skewness among attributes of the numeric type.
0.77
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
0.67
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-0.25
Mean kurtosis among attributes of the numeric type.
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.09
Third quartile of standard deviation of attributes of the numeric type.
0.89
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
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.13
Mean of means among attributes of the numeric type.
0.17
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.41
First quartile of kurtosis among attributes of the numeric type.
0.09
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
0.2
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
0.3
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.81
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of mutual information between the nominal attributes and the target attribute.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.77
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
0.67
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.89
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.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.89
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.
0.21
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.
0.04
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
0.2
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
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.5
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.77
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
0.24
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
10.05
Percentage of instances belonging to the most frequent class.
0.07
Mean standard deviation of attributes of the numeric type.
-0.25
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.32
Entropy of the target attribute values.
0.73
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
100515
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.11
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
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.15
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.81
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
0.66
Maximum kurtosis among attributes of the numeric type.
0.07
Minimum of means among attributes of the numeric type.
0.51
Second quartile (Median) of skewness among attributes of the numeric type.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.38
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.05
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.83
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 binary attributes.
Third quartile of entropy among attributes.
0.3
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.
-0.12
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
-0.06
Third quartile of kurtosis among attributes of the numeric type.
0.1
Average class difference between consecutive instances.
0.67
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.88
Maximum skewness among attributes of the numeric type.
0.04
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
0.16
Third quartile of means among attributes of the numeric type.
0.89
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
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.21
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.18
Maximum standard deviation of attributes of the numeric type.
9.95
Percentage of instances belonging to the least frequent class.
98.7
Percentage of numeric attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.2
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
0.3
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
99530
Number of instances belonging to the least frequent class.
1.3
Percentage of nominal attributes.

15 tasks

4 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
286 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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