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test_dataset

test_dataset

active ARFF Publicly available Visibility: public Uploaded 23-03-2019 by William Patterson
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Test dataset

61 features

class (target)numeric2 unique values
0 missing
V47numeric17 unique values
0 missing
V33numeric7461 unique values
14 missing
V34numeric5383 unique values
14 missing
V35numeric6702 unique values
14 missing
V36numeric6648 unique values
14 missing
V37numeric7262 unique values
14 missing
V38numeric6405 unique values
14 missing
V39numeric4767 unique values
14 missing
V40numeric5895 unique values
14 missing
V41numeric6944 unique values
14 missing
V42numeric15 unique values
0 missing
V43numeric20 unique values
0 missing
V44numeric15 unique values
0 missing
V45numeric16 unique values
0 missing
V46numeric9 unique values
0 missing
V31numeric7413 unique values
14 missing
V48numeric16 unique values
0 missing
V49numeric17 unique values
0 missing
V50numeric13 unique values
0 missing
V51numeric11 unique values
0 missing
V52numeric13 unique values
0 missing
V53numeric15 unique values
0 missing
V54numeric9 unique values
0 missing
V55numeric11 unique values
0 missing
V56numeric14 unique values
0 missing
V57numeric14 unique values
0 missing
V58numeric11 unique values
0 missing
V59numeric9 unique values
0 missing
V60numeric9 unique values
0 missing
V61numeric10 unique values
0 missing
V16numeric13 unique values
0 missing
V2numeric15 unique values
0 missing
V3numeric17 unique values
0 missing
V4numeric12 unique values
0 missing
V5numeric10 unique values
0 missing
V6numeric7 unique values
0 missing
V7numeric12 unique values
0 missing
V8numeric16 unique values
0 missing
V9numeric17 unique values
0 missing
V10numeric10 unique values
0 missing
V11numeric11 unique values
0 missing
V12numeric14 unique values
0 missing
V13numeric12 unique values
0 missing
V14numeric9 unique values
0 missing
V15numeric11 unique values
0 missing
V32numeric7973 unique values
14 missing
V17numeric14 unique values
0 missing
V18numeric11 unique values
0 missing
V19numeric6 unique values
0 missing
V20numeric8 unique values
0 missing
V21numeric9 unique values
0 missing
V22numeric7707 unique values
14 missing
V23numeric6800 unique values
14 missing
V24numeric6510 unique values
14 missing
V25numeric6630 unique values
14 missing
V26numeric5282 unique values
14 missing
V27numeric7394 unique values
14 missing
V28numeric6296 unique values
14 missing
V29numeric7337 unique values
14 missing
V30numeric5318 unique values
14 missing
Show all 61 features

62 properties

NumberOfInstances
15547
Number of instances (rows) of the dataset.
NumberOfFeatures
61
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
280
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
14
Number of instances with at least one value missing.
NumberOfNumericFeatures
61
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0.09
Percentage of instances having missing values.
PercentageOfMissingValues
0.03
Percentage of missing values.
PercentageOfNumericFeatures
100
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
2.52
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.04
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
Standard deviation of the number of distinct values among attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
1.25
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.03
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
5.32
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
0.05
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
1.62
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
0.04
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
10.99
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
0.06
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
2.16
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
0.05
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
1
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
0.07
Mean of means among attributes of the numeric type.
ClassEntropy
Entropy of the target attribute values.
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.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
152.29
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
1.51
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
10.47
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
0.5
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
12.17
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
0
Number of binary attributes.
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
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
1.85
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
0.05
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-2
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.01
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-0.05
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.01
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
Show all 62 properties

14 tasks

Supervised Regression on test_dataset
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on test_dataset
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on test_dataset
0 runs - estimation_procedure: Custom 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Regression on test_dataset
0 runs - estimation_procedure: Test on Training Data - evaluation_measure: predictive_accuracy - target_feature: class
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering
Clustering on test_dataset
0 runs - estimation_procedure: 50 times Clustering - target_feature: test
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