Data
BNG(anneal.ORIG,nominal,1000000)

BNG(anneal.ORIG,nominal,1000000)

active ARFF Publicly available Visibility: public Uploaded 08-04-2014 by Jan van Rijn
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39 features

class (target)nominal6 unique values
0 missing
familynominal9 unique values
0 missing
product-typenominal3 unique values
0 missing
steelnominal8 unique values
0 missing
carbonnominal3 unique values
0 missing
hardnessnominal3 unique values
0 missing
temper_rollingnominal1 unique values
0 missing
conditionnominal3 unique values
0 missing
formabilitynominal5 unique values
0 missing
strengthnominal3 unique values
0 missing
non-ageingnominal1 unique values
0 missing
surface-finishnominal2 unique values
0 missing
surface-qualitynominal4 unique values
0 missing
enamelabilitynominal5 unique values
0 missing
bcnominal1 unique values
0 missing
bfnominal1 unique values
0 missing
btnominal1 unique values
0 missing
bw%2Fmenominal2 unique values
0 missing
blnominal1 unique values
0 missing
mnominal1 unique values
0 missing
chromnominal1 unique values
0 missing
phosnominal1 unique values
0 missing
cbondnominal1 unique values
0 missing
marvinominal1 unique values
0 missing
exptlnominal1 unique values
0 missing
ferronominal1 unique values
0 missing
corrnominal1 unique values
0 missing
blue%2Fbright%2Fvarn%2Fcleannominal4 unique values
0 missing
lustrenominal1 unique values
0 missing
jurofmnominal1 unique values
0 missing
snominal1 unique values
0 missing
pnominal1 unique values
0 missing
shapenominal2 unique values
0 missing
thicknominal3 unique values
0 missing
widthnominal3 unique values
0 missing
lennominal3 unique values
0 missing
oilnominal2 unique values
0 missing
borenominal4 unique values
0 missing
packingnominal3 unique values
0 missing
Show all 39 features

107 properties

NumberOfInstances
1000000
Number of instances (rows) of the dataset.
NumberOfFeatures
39
Number of attributes (columns) of the dataset.
NumberOfClasses
6
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
39
Number of nominal attributes.
Quartile2AttributeEntropy
0.04
Second quartile (Median) of entropy among attributes.
REPTreeDepth2ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NKappa
0.6
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
kNN1NErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassPercentage
75.95
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
Mean standard deviation of attributes of the numeric type.
Quartile2KurtosisOfNumericAtts
Second quartile (Median) of kurtosis among attributes of the numeric type.
REPTreeDepth2Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
ClassEntropy
1.2
Entropy of the target attribute values.
kNN1NKappa
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
MajorityClassSize
759513
Number of instances belonging to the most frequent class.
MinAttributeEntropy
0
Minimal entropy among attributes.
Quartile2MeansOfNumericAtts
Second quartile (Median) of means among attributes of the numeric type.
REPTreeDepth3AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpAUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxAttributeEntropy
1.68
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
Minimum kurtosis among attributes of the numeric type.
Quartile2MutualInformation
0
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
REPTreeDepth3ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpErrRate
0.24
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxKurtosisOfNumericAtts
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
Minimum of means among attributes of the numeric type.
Quartile2SkewnessOfNumericAtts
Second quartile (Median) of skewness among attributes of the numeric type.
REPTreeDepth3Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
DecisionStumpKappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
MaxMeansOfNumericAtts
Maximum of means among attributes of the numeric type.
MinMutualInformation
0
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
10.26
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
Second quartile (Median) of standard deviation of attributes of the numeric type.
RandomTreeDepth1AUC
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Dimensionality
0
Number of attributes divided by the number of instances.
MaxMutualInformation
0.22
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
1
The minimal number of distinct values among attributes of the nominal type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
0.53
Third quartile of entropy among attributes.
RandomTreeDepth1ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
EquivalentNumberOfAtts
47.7
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MaxNominalAttDistinctValues
9
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
Minimum skewness among attributes of the numeric type.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
Third quartile of kurtosis among attributes of the numeric type.
AutoCorrelation
0.6
Average class difference between consecutive instances.
RandomTreeDepth1Kappa
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
J48.00001.AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxSkewnessOfNumericAtts
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
Minimum standard deviation of attributes of the numeric type.
PercentageOfNumericFeatures
0
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
Third quartile of means among attributes of the numeric type.
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
RandomTreeDepth2AUC
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MaxStdDevOfNumericAtts
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
0.06
Percentage of instances belonging to the least frequent class.
PercentageOfSymbolicFeatures
100
Percentage of nominal attributes.
Quartile3MutualInformation
0.03
Third quartile of mutual information between the nominal attributes and the target attribute.
CfsSubsetEval_DecisionStumpErrRate
0.15
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
RandomTreeDepth2ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.00001.Kappa
0.71
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
MeanAttributeEntropy
0.36
Average entropy of the attributes.
MinorityClassSize
597
Number of instances belonging to the least frequent class.
Quartile1AttributeEntropy
0
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
Third quartile of skewness among attributes of the numeric type.
CfsSubsetEval_DecisionStumpKappa
0.6
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
RandomTreeDepth2Kappa
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
J48.0001.AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanKurtosisOfNumericAtts
Mean kurtosis among attributes of the numeric type.
NaiveBayesAUC
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1KurtosisOfNumericAtts
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
Third quartile of standard deviation of attributes of the numeric type.
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
RandomTreeDepth3AUC
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMeansOfNumericAtts
Mean of means among attributes of the numeric type.
NaiveBayesErrRate
0.17
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MeansOfNumericAtts
First quartile of means among attributes of the numeric type.
REPTreeDepth1AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesErrRate
0.15
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
RandomTreeDepth3ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.0001.Kappa
0.71
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
MeanMutualInformation
0.03
Average mutual information between the nominal attributes and the target attribute.
NaiveBayesKappa
0.57
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Quartile1MutualInformation
0
First quartile of mutual information between the nominal attributes and the target attribute.
REPTreeDepth1ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
CfsSubsetEval_NaiveBayesKappa
0.6
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
RandomTreeDepth3Kappa
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
J48.001.AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNoiseToSignalRatio
13.18
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
NumberOfBinaryFeatures
4
Number of binary attributes.
Quartile1SkewnessOfNumericAtts
First quartile of skewness among attributes of the numeric type.
REPTreeDepth1Kappa
0.7
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
StdvNominalAttDistinctValues
1.97
Standard deviation of the number of distinct values among attributes of the nominal type.
J48.001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanNominalAttDistinctValues
2.51
Average number of distinct values among the attributes of the nominal type.
Quartile1StdDevOfNumericAtts
First quartile of standard deviation of attributes of the numeric type.
REPTreeDepth2AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
CfsSubsetEval_kNN1NErrRate
0.15
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
kNN1NAUC
0.94
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
J48.001.Kappa
0.71
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MeanSkewnessOfNumericAtts
Mean skewness among attributes of the numeric type.
Show all 107 properties

26 tasks

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