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pbc

pbc

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Felicia West
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  • binarized mythbusting_1 study_1 study_123 study_15 study_20 study_41
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Author: Source: Unknown - Date unknown Please cite: Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a lower target value as positive ('P') and all others as negative ('N').

19 features

binaryClass (target)nominal2 unique values
0 missing
Z9numeric201 unique values
134 missing
Z17nominal4 unique values
106 missing
Z16numeric48 unique values
2 missing
Z15numeric243 unique values
11 missing
Z14numeric146 unique values
136 missing
Z13numeric179 unique values
106 missing
Z12numeric295 unique values
106 missing
Z11numeric158 unique values
108 missing
Z10numeric154 unique values
0 missing
Dnominal2 unique values
0 missing
Z8numeric98 unique values
0 missing
Z7nominal3 unique values
0 missing
Z6nominal2 unique values
106 missing
Z5nominal2 unique values
106 missing
Z4nominal2 unique values
106 missing
Z3nominal2 unique values
106 missing
Z2numeric345 unique values
0 missing
Z1nominal2 unique values
106 missing
Show all 19 features

107 properties

NumberOfInstances
418
Number of instances (rows) of the dataset.
NumberOfFeatures
19
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
1239
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
142
Number of instances with at least one value missing.
NumberOfNumericFeatures
10
Number of numeric attributes.
NumberOfSymbolicFeatures
9
Number of nominal attributes.
AutoCorrelation
0.63
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.69
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
0.33
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
0.33
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
0.69
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
0.33
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
0.33
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
0.69
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
0.33
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
0.33
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
0.99
Entropy of the target attribute values.
DecisionStumpAUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.39
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.05
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
27.94
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.34
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.34
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.34
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
55.02
Percentage of instances belonging to the most frequent class.
MajorityClassSize
230
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.61
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
14.34
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
1982.66
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.06
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
3.41
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
2140.39
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
0.94
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
6.67
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
302.23
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.04
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
25.53
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2.33
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
1.79
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
269.44
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.42
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.62
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
3.22
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
-0.47
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.42
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
44.98
Percentage of instances belonging to the least frequent class.
MinorityClassSize
188
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.33
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
7
Number of binary attributes.
PercentageOfBinaryFeatures
36.84
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
33.97
Percentage of instances having missing values.
PercentageOfMissingValues
15.6
Percentage of missing values.
PercentageOfNumericFeatures
52.63
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
47.37
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.79
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
0.79
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
8.92
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
0.49
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
3.56
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
0.95
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
7.84
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
110.1
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.04
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
2.26
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
60.92
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
0.99
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
10.48
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
285.15
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.06
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
2.79
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
131.73
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.33
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.33
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.7
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.33
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.35
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.38
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.38
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.38
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0.71
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.4
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

15 tasks

Supervised Classification on pbc
508 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on pbc
215 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: binaryClass
Supervised Classification on pbc
0 runs - estimation_procedure: 33% Holdout set - target_feature: binaryClass
Supervised Data Stream Classification on pbc
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: binaryClass
Clustering on pbc
0 runs
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
Clustering on pbc
0 runs - estimation_procedure: 50 times Clustering
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