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BNG(anneal)

BNG(anneal)

active ARFF Publicly available Visibility: public Uploaded 06-10-2016 by Jan van Rijn
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Automated file upload of BNG(anneal)

39 features

class (target)nominal6 unique values
0 missing
familynominal10 unique values
0 missing
product-typenominal3 unique values
0 missing
steelnominal9 unique values
0 missing
carbonnumeric94197 unique values
0 missing
hardnessnumeric119264 unique values
0 missing
temper_rollingnominal2 unique values
0 missing
conditionnominal4 unique values
0 missing
formabilitynominal6 unique values
0 missing
strengthnumeric74930 unique values
0 missing
non-ageingnominal2 unique values
0 missing
surface-finishnominal3 unique values
0 missing
surface-qualitynominal5 unique values
0 missing
enamelabilitynominal6 unique values
0 missing
bcnominal2 unique values
0 missing
bfnominal2 unique values
0 missing
btnominal2 unique values
0 missing
bw_menominal3 unique values
0 missing
blnominal2 unique values
0 missing
mnominal2 unique values
0 missing
chromnominal2 unique values
0 missing
phosnominal2 unique values
0 missing
cbondnominal2 unique values
0 missing
marvinominal2 unique values
0 missing
exptlnominal2 unique values
0 missing
ferronominal2 unique values
0 missing
corrnominal2 unique values
0 missing
blue_bright_varn_cleannominal5 unique values
0 missing
lustrenominal2 unique values
0 missing
jurofmnominal2 unique values
0 missing
snominal2 unique values
0 missing
pnominal2 unique values
0 missing
shapenominal2 unique values
0 missing
thicknumeric720607 unique values
0 missing
widthnumeric586468 unique values
0 missing
lennumeric194388 unique values
0 missing
oilnominal3 unique values
0 missing
borenominal4 unique values
0 missing
packingnominal4 unique values
0 missing
Show all 39 features

62 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
6
Number of numeric attributes.
NumberOfSymbolicFeatures
33
Number of nominal attributes.
MaxSkewnessOfNumericAtts
2.97
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.88
Minimum standard deviation of attributes of the numeric type.
Quartile1AttributeEntropy
0.05
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
2.96
Third quartile of skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
1891.67
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
0.06
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
-0.47
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
778.56
Third quartile of standard deviation of attributes of the numeric type.
MeanAttributeEntropy
0.57
Average entropy of the attributes.
MinorityClassSize
555
Number of instances belonging to the least frequent class.
Quartile1MeansOfNumericAtts
4.28
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
2.08
Standard deviation of the number of distinct values among attributes of the nominal type.
MeanKurtosisOfNumericAtts
2.57
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
19
Number of binary attributes.
Quartile1MutualInformation
0.01
First quartile of mutual information between the nominal attributes and the target attribute.
MeanMeansOfNumericAtts
365.88
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
0.91
First quartile of skewness among attributes of the numeric type.
MeanMutualInformation
0.06
Average mutual information between the nominal attributes and the target attribute.
Quartile1StdDevOfNumericAtts
12.42
First quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
0.6
Average class difference between consecutive instances.
MeanNoiseToSignalRatio
8.29
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Quartile2AttributeEntropy
0.38
Second quartile (Median) of entropy among attributes.
ClassEntropy
1.2
Entropy of the target attribute values.
MeanNominalAttDistinctValues
3.3
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
0.99
Second quartile (Median) of kurtosis among attributes of the numeric type.
Dimensionality
0
Number of attributes divided by the number of instances.
MeanSkewnessOfNumericAtts
1.69
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
30.26
Second quartile (Median) of means among attributes of the numeric type.
EquivalentNumberOfAtts
19.63
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
75.97
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
413.68
Mean standard deviation of attributes of the numeric type.
Quartile2MutualInformation
0.02
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
MajorityClassSize
759652
Number of instances belonging to the most frequent class.
MinAttributeEntropy
0.03
Minimal entropy among attributes.
Quartile2SkewnessOfNumericAtts
1.46
Second quartile (Median) of skewness among attributes of the numeric type.
MaxAttributeEntropy
2.17
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-0.88
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
48.72
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
82.88
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxKurtosisOfNumericAtts
7.43
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
1.2
Minimum of means among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
0.8
Third quartile of entropy among attributes.
MaxMeansOfNumericAtts
1341.59
Maximum of means among attributes of the numeric type.
MinMutualInformation
0
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
7.28
Third quartile of kurtosis among attributes of the numeric type.
MaxMutualInformation
0.39
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
PercentageOfNumericFeatures
15.38
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
925.4
Third quartile of means among attributes of the numeric type.
MaxNominalAttDistinctValues
10
The maximum number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
0.08
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
84.62
Percentage of nominal attributes.
Quartile3MutualInformation
0.08
Third quartile of mutual information between the nominal attributes and the target attribute.
Show all 62 properties

22 tasks

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