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BNG(credit-g)

BNG(credit-g)

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21 features

class (target)nominal2 unique values
0 missing
residence_sincenumeric4 unique values
0 missing
foreign_workernominal2 unique values
0 missing
own_telephonenominal2 unique values
0 missing
num_dependentsnumeric2 unique values
0 missing
jobnominal4 unique values
0 missing
existing_creditsnumeric4 unique values
0 missing
housingnominal3 unique values
0 missing
other_payment_plansnominal3 unique values
0 missing
agenumeric983864 unique values
0 missing
property_magnitudenominal4 unique values
0 missing
checking_statusnominal4 unique values
0 missing
other_partiesnominal3 unique values
0 missing
personal_statusnominal5 unique values
0 missing
installment_commitmentnumeric4 unique values
0 missing
employmentnominal5 unique values
0 missing
savings_statusnominal5 unique values
0 missing
credit_amountnumeric999900 unique values
0 missing
purposenominal11 unique values
0 missing
credit_historynominal5 unique values
0 missing
durationnumeric971857 unique values
0 missing
Show all 21 features

107 properties

NumberOfInstances
1000000
Number of instances (rows) of the dataset.
NumberOfFeatures
21
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
7
Number of numeric attributes.
NumberOfSymbolicFeatures
14
Number of nominal attributes.
AutoCorrelation
0.58
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.78
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
CfsSubsetEval_DecisionStumpErrRate
0.23
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
CfsSubsetEval_DecisionStumpKappa
0.4
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
CfsSubsetEval_NaiveBayesAUC
0.78
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
CfsSubsetEval_NaiveBayesErrRate
0.23
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
CfsSubsetEval_NaiveBayesKappa
0.4
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
CfsSubsetEval_kNN1NAUC
0.78
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
CfsSubsetEval_kNN1NErrRate
0.23
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
CfsSubsetEval_kNN1NKappa
0.4
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
ClassEntropy
0.88
Entropy of the target attribute values.
DecisionStumpAUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
45.19
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.44
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.44
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.44
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
69.98
Percentage of instances belonging to the most frequent class.
MajorityClassSize
699774
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
2.69
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
2.67
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
3210.12
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.09
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
11
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
1.88
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
2779.72
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1.44
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
0.65
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
467.86
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.02
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
73.03
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
4.14
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.89
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
400.9
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.24
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.38
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
1.16
Minimum of means among attributes of the numeric type.
MinMutualInformation
0
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.51
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.36
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
30.02
Percentage of instances belonging to the least frequent class.
MinorityClassSize
300226
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.23
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
3
Number of binary attributes.
PercentageOfBinaryFeatures
14.29
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
33.33
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
66.67
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.92
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-1.22
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
1.43
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
-0.26
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.61
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.55
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
0.45
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
2.95
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.01
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
1.03
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
1.12
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
1.88
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
2.2
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
35.63
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.02
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
1.76
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
12.06
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.8
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.23
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.43
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.8
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.23
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.43
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.8
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.23
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.43
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.28
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.28
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.28
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
2.28
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.31
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

25 tasks

Supervised Classification on BNG(credit-g)
21 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(credit-g)
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(credit-g)
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Learning Curve on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(credit-g)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on BNG(credit-g)
204 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on BNG(credit-g)
0 runs
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(credit-g)
0 runs - estimation_procedure: 50 times Clustering
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