DEVELOPMENT... OpenML
Data
BNG(mfeat-zernike)

BNG(mfeat-zernike)

active ARFF Publicly available Visibility: public Uploaded 28-04-2014 by unknown
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit

48 features

class (target)nominal10 unique values
0 missing
att26numeric978984 unique values
0 missing
att25numeric743330 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
att13numeric997844 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
att1numeric230641 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
Show all 48 features

107 properties

NumberOfInstances
1000000
Number of instances (rows) of the dataset.
NumberOfFeatures
48
Number of attributes (columns) of the dataset.
NumberOfClasses
10
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
47
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.1
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
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
CfsSubsetEval_DecisionStumpErrRate
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
CfsSubsetEval_DecisionStumpKappa
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
CfsSubsetEval_NaiveBayesAUC
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
CfsSubsetEval_NaiveBayesErrRate
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
CfsSubsetEval_NaiveBayesKappa
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
CfsSubsetEval_kNN1NAUC
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
CfsSubsetEval_kNN1NErrRate
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
CfsSubsetEval_kNN1NKappa
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
ClassEntropy
3.32
Entropy of the target attribute values.
DecisionStumpAUC
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.81
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.29
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
10.03
Percentage of instances belonging to the most frequent class.
MajorityClassSize
100289
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
2.23
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
507.71
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
10
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
1.5
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
124.19
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
0.29
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
88.12
Mean of means among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
10
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.75
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
39.71
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.98
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.08
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
10
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
0.02
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.07
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
9.98
Percentage of instances belonging to the least frequent class.
MinorityClassSize
99797
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.31
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.66
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
97.92
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
2.08
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.56
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
7.32
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
0.38
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
3.52
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
0.02
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
68.78
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0.74
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
37.1
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
1.12
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
126.53
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
1.13
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
64.83
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.35
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.35
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.35
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

25 tasks

Supervised Classification on BNG(mfeat-zernike)
6 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(mfeat-zernike)
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Learning Curve on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on BNG(mfeat-zernike)
46 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on BNG(mfeat-zernike)
0 runs
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike)
0 runs - estimation_procedure: 50 times Clustering
Define a new task