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BNG(letter,1000,5)

BNG(letter,1000,5)

active ARFF public domain Visibility: public Uploaded 22-02-2015 by unknown
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17 features

class (target)nominal26 unique values
0 missing
y2barnumeric617179 unique values
0 missing
yegvxnumeric354809 unique values
0 missing
y-egenumeric631136 unique values
0 missing
xegvynumeric340136 unique values
0 missing
x-egenumeric507072 unique values
0 missing
xy2brnumeric382305 unique values
0 missing
x2ybrnumeric568783 unique values
0 missing
xybarnumeric571179 unique values
0 missing
x-boxnumeric394485 unique values
0 missing
x2barnumeric612026 unique values
0 missing
y-barnumeric516094 unique values
0 missing
x-barnumeric373660 unique values
0 missing
onpixnumeric517343 unique values
0 missing
highnumeric637456 unique values
0 missing
widthnumeric395679 unique values
0 missing
y-boxnumeric833612 unique values
0 missing
Show all 17 features

107 properties

NumberOfInstances
1000000
Number of instances (rows) of the dataset.
NumberOfFeatures
17
Number of attributes (columns) of the dataset.
NumberOfClasses
26
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
16
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.04
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.68
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
0.64
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
0.34
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
0.68
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
0.64
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
0.34
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
0.68
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
0.64
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
0.34
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
4.7
Entropy of the target attribute values.
DecisionStumpAUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.94
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.02
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
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.58
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.4
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.58
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.4
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.58
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.4
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
4.08
Percentage of instances belonging to the most frequent class.
MajorityClassSize
40765
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
1.15
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
8.65
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
26
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
1.06
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
3.37
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
0.13
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
5.98
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
26
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.27
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
2.27
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.63
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
3.2
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
26
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.29
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
1.66
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
3.68
Percentage of instances belonging to the least frequent class.
MinorityClassSize
36811
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.74
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.23
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
94.12
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
5.88
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.3
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
4.16
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
-0.13
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
2.02
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
0.06
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
5.94
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
0.22
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
2.2
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
0.42
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
7.83
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
0.6
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
2.47
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.56
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.56
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.56
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.64
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.64
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.64
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.33
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
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.65
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

21 tasks

Supervised Classification on BNG(letter,1000,5)
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Learning Curve on BNG(letter,1000,5)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(letter,1000,5)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(letter,1000,5)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(letter,1000,5)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(letter,1000,5)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(letter,1000,5)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(letter,1000,5)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on BNG(letter,1000,5)
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on BNG(letter,1000,5)
30 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on BNG(letter,1000,5)
0 runs
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
Clustering on BNG(letter,1000,5)
0 runs - estimation_procedure: 50 times Clustering
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