DEVELOPMENT... OpenML
Data
BNG(optdigits)

BNG(optdigits)

active ARFF Publicly available Visibility: public Uploaded 06-10-2016 by Jason
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
Automated file upload of BNG(optdigits)

65 features

class (target)nominal10 unique values
0 missing
input48nominal3 unique values
0 missing
input34nominal3 unique values
0 missing
input47nominal3 unique values
0 missing
input46nominal3 unique values
0 missing
input45nominal3 unique values
0 missing
input44nominal3 unique values
0 missing
input43nominal3 unique values
0 missing
input42nominal3 unique values
0 missing
input41nominal3 unique values
0 missing
input40nominal1 unique values
0 missing
input39nominal3 unique values
0 missing
input38nominal3 unique values
0 missing
input37nominal3 unique values
0 missing
input36nominal3 unique values
0 missing
input35nominal3 unique values
0 missing
input33nominal3 unique values
0 missing
input49nominal3 unique values
0 missing
input50nominal3 unique values
0 missing
input51nominal3 unique values
0 missing
input52nominal3 unique values
0 missing
input53nominal3 unique values
0 missing
input54nominal3 unique values
0 missing
input55nominal3 unique values
0 missing
input56nominal3 unique values
0 missing
input57nominal3 unique values
0 missing
input58nominal3 unique values
0 missing
input59nominal3 unique values
0 missing
input60nominal3 unique values
0 missing
input61nominal3 unique values
0 missing
input62nominal3 unique values
0 missing
input63nominal3 unique values
0 missing
input64nominal3 unique values
0 missing
input17nominal3 unique values
0 missing
input2nominal3 unique values
0 missing
input3nominal3 unique values
0 missing
input4nominal3 unique values
0 missing
input5nominal3 unique values
0 missing
input6nominal3 unique values
0 missing
input7nominal3 unique values
0 missing
input8nominal3 unique values
0 missing
input9nominal3 unique values
0 missing
input10nominal3 unique values
0 missing
input11nominal3 unique values
0 missing
input12nominal3 unique values
0 missing
input13nominal3 unique values
0 missing
input14nominal3 unique values
0 missing
input15nominal3 unique values
0 missing
input16nominal3 unique values
0 missing
input1nominal1 unique values
0 missing
input18nominal3 unique values
0 missing
input19nominal3 unique values
0 missing
input20nominal3 unique values
0 missing
input21nominal3 unique values
0 missing
input22nominal3 unique values
0 missing
input23nominal3 unique values
0 missing
input24nominal3 unique values
0 missing
input25nominal3 unique values
0 missing
input26nominal3 unique values
0 missing
input27nominal3 unique values
0 missing
input28nominal3 unique values
0 missing
input29nominal3 unique values
0 missing
input30nominal3 unique values
0 missing
input31nominal3 unique values
0 missing
input32nominal3 unique values
0 missing
Show all 65 features

62 properties

NumberOfInstances
1000000
Number of instances (rows) of the dataset.
NumberOfFeatures
65
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
65
Number of nominal attributes.
Quartile1MutualInformation
0.02
First quartile of mutual information between the nominal attributes and the target attribute.
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
0.21
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.
StdvNominalAttDistinctValues
0.94
Standard deviation of the number of distinct values among attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.17
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
0.2
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
1.47
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
0.29
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.
AutoCorrelation
0.1
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
Mean of means among attributes of the numeric type.
ClassEntropy
3.32
Entropy of the target attribute values.
Dimensionality
0
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
18.37
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
10.17
Percentage of instances belonging to the most frequent class.
MajorityClassSize
101675
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.55
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.49
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
0.92
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
MeanMutualInformation
0.18
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
3.05
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
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
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
1
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
9.86
Percentage of instances belonging to the least frequent class.
MinorityClassSize
98637
Number of instances belonging to the least frequent class.
Show all 62 properties

21 tasks

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