DEVELOPMENT... OpenML
Data
BNG(mfeat-zernike,nominal,1000000)

BNG(mfeat-zernike,nominal,1000000)

active ARFF Publicly available Visibility: public Uploaded 08-04-2014 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
att26nominal3 unique values
0 missing
att25nominal3 unique values
0 missing
att27nominal3 unique values
0 missing
att28nominal3 unique values
0 missing
att29nominal3 unique values
0 missing
att30nominal3 unique values
0 missing
att31nominal3 unique values
0 missing
att32nominal3 unique values
0 missing
att33nominal3 unique values
0 missing
att34nominal3 unique values
0 missing
att35nominal3 unique values
0 missing
att36nominal3 unique values
0 missing
att37nominal3 unique values
0 missing
att38nominal3 unique values
0 missing
att39nominal3 unique values
0 missing
att40nominal3 unique values
0 missing
att41nominal3 unique values
0 missing
att42nominal3 unique values
0 missing
att43nominal3 unique values
0 missing
att44nominal3 unique values
0 missing
att45nominal3 unique values
0 missing
att46nominal3 unique values
0 missing
att47nominal3 unique values
0 missing
att13nominal3 unique values
0 missing
att2nominal3 unique values
0 missing
att3nominal3 unique values
0 missing
att4nominal3 unique values
0 missing
att5nominal3 unique values
0 missing
att6nominal3 unique values
0 missing
att7nominal3 unique values
0 missing
att8nominal3 unique values
0 missing
att9nominal3 unique values
0 missing
att10nominal3 unique values
0 missing
att11nominal3 unique values
0 missing
att12nominal3 unique values
0 missing
att1nominal3 unique values
0 missing
att14nominal3 unique values
0 missing
att15nominal3 unique values
0 missing
att16nominal3 unique values
0 missing
att17nominal3 unique values
0 missing
att18nominal3 unique values
0 missing
att19nominal3 unique values
0 missing
att20nominal3 unique values
0 missing
att21nominal3 unique values
0 missing
att22nominal3 unique values
0 missing
att23nominal3 unique values
0 missing
att24nominal3 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
0
Number of numeric attributes.
NumberOfSymbolicFeatures
48
Number of nominal attributes.
AutoCorrelation
0.1
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.93
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
0.74
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
0.93
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
0.74
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
0.93
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
0.74
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
14.93
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.92
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
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.92
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
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.92
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
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
10.04
Percentage of instances belonging to the most frequent class.
MajorityClassSize
100380
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.51
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.52
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
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1.13
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
Mean of means among attributes of the numeric type.
MeanMutualInformation
0.22
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
4.08
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
3.15
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.51
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
Minimum of means among attributes of the numeric type.
MinMutualInformation
0.04
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
3
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
9.94
Percentage of instances belonging to the least frequent class.
MinorityClassSize
99430
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.26
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.72
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
0
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
100
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.99
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
0.11
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.2
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.21
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
1.34
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.31
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.75
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
1.01
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.22
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

26 tasks

Supervised Classification on BNG(mfeat-zernike,nominal,1000000)
5 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on BNG(mfeat-zernike,nominal,1000000)
46 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(mfeat-zernike,nominal,1000000)
0 runs - estimation_procedure: 50 times Clustering
Define a new task