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BNG(cmc)

BNG(cmc)

active ARFF Publicly available Visibility: public Uploaded 28-04-2014 by Jason
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10 features

Contraceptive_method_used (target)nominal3 unique values
0 missing
Wifes_agenumeric55249 unique values
0 missing
Wifes_educationnominal4 unique values
0 missing
Husbands_educationnominal4 unique values
0 missing
Number_of_children_ever_bornnumeric34844 unique values
0 missing
Wifes_religionnominal2 unique values
0 missing
Wifes_now_working%3Fnominal2 unique values
0 missing
Husbands_occupationnominal4 unique values
0 missing
Standard-of-living_indexnominal4 unique values
0 missing
Media_exposurenominal2 unique values
0 missing
Show all 10 features

107 properties

NumberOfInstances
55296
Number of instances (rows) of the dataset.
NumberOfFeatures
10
Number of attributes (columns) of the dataset.
NumberOfClasses
3
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
2
Number of numeric attributes.
NumberOfSymbolicFeatures
8
Number of nominal attributes.
AutoCorrelation
0.36
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.71
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
0.44
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
0.31
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
0.71
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
0.44
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
0.31
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
0.71
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
0.44
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
0.31
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
1.54
Entropy of the target attribute values.
DecisionStumpAUC
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.55
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.15
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
54.03
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.31
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.31
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.44
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.31
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
42.62
Percentage of instances belonging to the most frequent class.
MajorityClassSize
23567
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.87
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
0.77
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
32.56
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.07
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
4
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
1.01
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
8.23
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1.23
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
-0.09
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
17.91
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.03
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
42.2
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
3.13
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.63
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
5.28
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.39
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.96
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
3.26
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
0.26
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
2.34
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
22.51
Percentage of instances belonging to the least frequent class.
MinorityClassSize
12447
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.49
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
3
Number of binary attributes.
PercentageOfBinaryFeatures
30
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
20
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
80
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.61
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.96
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
3.26
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0.01
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
2.34
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.47
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
-0.09
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
17.91
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.03
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0.63
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
5.28
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
1.77
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
0.77
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
32.56
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.04
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
1.01
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
8.23
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.45
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.45
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.45
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0.99
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.53
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.18
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

16 tasks

Supervised Classification on BNG(cmc)
252 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
Supervised Classification on BNG(cmc)
196 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
Supervised Classification on BNG(cmc)
159 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
Learning Curve on BNG(cmc)
67 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
Supervised Data Stream Classification on BNG(cmc)
291 runs - estimation_procedure: Interleaved Test then Train - target_feature: Contraceptive_method_used
Clustering on BNG(cmc)
0 runs
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(cmc)
0 runs - estimation_procedure: 50 times Clustering
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