DEVELOPMENT... OpenML
Data
GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1

GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1

active ARFF public Visibility: public Uploaded 06-04-2017 by Arnold
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
GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1-pmlb

21 features

class (target)nominal2 unique values
0 missing
N10nominal2 unique values
0 missing
P2nominal3 unique values
0 missing
P1nominal3 unique values
0 missing
N17nominal3 unique values
0 missing
N16nominal3 unique values
0 missing
N15nominal3 unique values
0 missing
N14nominal3 unique values
0 missing
N13nominal3 unique values
0 missing
N12nominal3 unique values
0 missing
N11nominal3 unique values
0 missing
N0nominal2 unique values
0 missing
N9nominal3 unique values
0 missing
N8nominal3 unique values
0 missing
N7nominal3 unique values
0 missing
N6nominal3 unique values
0 missing
N5nominal3 unique values
0 missing
N4nominal3 unique values
0 missing
N3nominal3 unique values
0 missing
N2nominal3 unique values
0 missing
N1nominal3 unique values
0 missing
Show all 21 features

62 properties

NumberOfInstances
1600
Number of instances (rows) of the dataset.
NumberOfFeatures
21
Number of attributes (columns) of the dataset.
NumberOfClasses
2
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
21
Number of nominal attributes.
Quartile1MutualInformation
0
First quartile of mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
14.29
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
0.93
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
0.36
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
1.19
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
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
1.45
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
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
1
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
Mean of means among attributes of the numeric type.
ClassEntropy
1
Entropy of the target attribute values.
Dimensionality
0.01
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
1708.23
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
50
Percentage of instances belonging to the most frequent class.
MajorityClassSize
800
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.5
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
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
3
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
1.1
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
3
Number of binary attributes.
MeanMutualInformation
0
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
1870.29
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2.86
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
0.14
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
2
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
50
Percentage of instances belonging to the least frequent class.
MinorityClassSize
800
Number of instances belonging to the least frequent class.
Show all 62 properties

23 tasks

Supervised Classification on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 33% Holdout set - target_feature: class
Supervised Classification on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Clustering on GAMETES_Epistasis_2-Way_20atts_0.4H_EDM-1_1
0 runs - estimation_procedure: 50 times Clustering
Define a new task