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SVHN_small

SVHN_small

active ARFF Publicly available Visibility: public Uploaded 18-09-2019 by Joaquin Vanschoren
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10% stratified subsample of the original SVHN data

3073 features

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Show first 100 features

62 properties

NumberOfInstances
9927
Number of instances (rows) of the dataset.
NumberOfFeatures
3073
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
3072
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
ClassEntropy
3.22
Entropy of the target attribute values.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Dimensionality
0.31
Number of attributes divided by the number of instances.
MeanNominalAttDistinctValues
10
Average number of distinct values among the attributes of the nominal type.
Quartile2KurtosisOfNumericAtts
-0.44
Second quartile (Median) of kurtosis among attributes of the numeric type.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MeanSkewnessOfNumericAtts
0.36
Mean skewness among attributes of the numeric type.
Quartile2MeansOfNumericAtts
113.55
Second quartile (Median) of means among attributes of the numeric type.
MajorityClassPercentage
19.1
Percentage of instances belonging to the most frequent class.
MeanStdDevOfNumericAtts
52.53
Mean standard deviation of attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
MajorityClassSize
1896
Number of instances belonging to the most frequent class.
MinAttributeEntropy
Minimal entropy among attributes.
Quartile2SkewnessOfNumericAtts
0.35
Second quartile (Median) of skewness among attributes of the numeric type.
MaxAttributeEntropy
Maximum entropy among attributes.
MinKurtosisOfNumericAtts
-0.71
Minimum kurtosis among attributes of the numeric type.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
Quartile2StdDevOfNumericAtts
53.13
Second quartile (Median) of standard deviation of attributes of the numeric type.
MaxKurtosisOfNumericAtts
0.18
Maximum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
108.36
Minimum of means among attributes of the numeric type.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
MaxMeansOfNumericAtts
123.56
Maximum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
PercentageOfMissingValues
0
Percentage of missing values.
Quartile3KurtosisOfNumericAtts
-0.33
Third quartile of kurtosis among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
10
The minimal number of distinct values among attributes of the nominal type.
PercentageOfNumericFeatures
99.97
Percentage of numeric attributes.
Quartile3MeansOfNumericAtts
118.54
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
0.19
Minimum skewness among attributes of the numeric type.
PercentageOfSymbolicFeatures
0.03
Percentage of nominal attributes.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
MaxSkewnessOfNumericAtts
0.6
Maximum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
46.95
Minimum standard deviation of attributes of the numeric type.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile3SkewnessOfNumericAtts
0.4
Third quartile of skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
56.98
Maximum standard deviation of attributes of the numeric type.
MinorityClassPercentage
6.3
Percentage of instances belonging to the least frequent class.
Quartile1KurtosisOfNumericAtts
-0.51
First quartile of kurtosis among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
53.93
Third quartile of standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MinorityClassSize
625
Number of instances belonging to the least frequent class.
Quartile1MeansOfNumericAtts
112.53
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
MeanKurtosisOfNumericAtts
-0.39
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
MeanMeansOfNumericAtts
115
Mean of means among attributes of the numeric type.
Quartile1SkewnessOfNumericAtts
0.32
First quartile of skewness among attributes of the numeric type.
AutoCorrelation
1
Average class difference between consecutive instances.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
Quartile1StdDevOfNumericAtts
51.18
First quartile of standard deviation of attributes of the numeric type.
Show all 62 properties

11 tasks

Learning Curve on SVHN_small
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on SVHN_small
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on SVHN_small
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on SVHN_small
0 runs - estimation_procedure: 50 times Clustering
Clustering on SVHN_small
0 runs - estimation_procedure: 50 times Clustering
Clustering on SVHN_small
0 runs - estimation_procedure: 50 times Clustering
Clustering on SVHN_small
0 runs - estimation_procedure: 50 times Clustering
Clustering on SVHN_small
0 runs - estimation_procedure: 50 times Clustering
Clustering on SVHN_small
0 runs - estimation_procedure: 50 times Clustering
Clustering on SVHN_small
0 runs - estimation_procedure: 50 times Clustering
Clustering on SVHN_small
0 runs - estimation_procedure: 50 times Clustering
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