DEVELOPMENT... OpenML
Data
calendarDOW

calendarDOW

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
calendarDOW-pmlb

33 features

class (target)nominal5 unique values
0 missing
Feature17nominal7 unique values
0 missing
Feature16nominal7 unique values
0 missing
Feature18numeric51 unique values
0 missing
Feature19numeric90 unique values
0 missing
Feature20nominal4 unique values
0 missing
Feature21numeric14 unique values
0 missing
Feature22nominal3 unique values
0 missing
Feature23numeric21 unique values
0 missing
Feature24nominal2 unique values
0 missing
Feature25nominal2 unique values
0 missing
Feature26nominal3 unique values
0 missing
Feature27nominal3 unique values
0 missing
Feature28nominal9 unique values
0 missing
Feature29nominal9 unique values
0 missing
Feature30numeric15 unique values
0 missing
Feature31nominal3 unique values
0 missing
Feature00numeric24 unique values
0 missing
Feature15nominal7 unique values
0 missing
Feature14nominal7 unique values
0 missing
Feature13numeric70 unique values
0 missing
Feature12numeric46 unique values
0 missing
Feature11nominal6 unique values
0 missing
Feature10nominal6 unique values
0 missing
Feature09nominal6 unique values
0 missing
Feature08nominal9 unique values
0 missing
Feature07numeric18 unique values
0 missing
Feature06numeric16 unique values
0 missing
Feature05nominal8 unique values
0 missing
Feature04numeric13 unique values
0 missing
Feature03nominal8 unique values
0 missing
Feature02nominal10 unique values
0 missing
Feature01numeric32 unique values
0 missing
Show all 33 features

62 properties

NumberOfInstances
399
Number of instances (rows) of the dataset.
NumberOfFeatures
33
Number of attributes (columns) of the dataset.
NumberOfClasses
5
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
12
Number of numeric attributes.
NumberOfSymbolicFeatures
21
Number of nominal attributes.
Quartile1MutualInformation
0.07
First quartile of mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
6.06
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
36.36
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
63.64
Percentage of nominal attributes.
Quartile1AttributeEntropy
1.38
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
0.09
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
13.02
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
2.53
Standard deviation of the number of distinct values among attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
-3.05
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
2.9
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.91
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
1.29
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
18.52
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.17
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
-1.53
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
5.33
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
2.1
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
10.34
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
40.24
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.26
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
-1.19
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
14.73
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
0.39
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
26.32
Mean of means among attributes of the numeric type.
ClassEntropy
2.28
Entropy of the target attribute values.
Dimensionality
0.08
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
11.58
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
24.06
Percentage of instances belonging to the most frequent class.
MajorityClassSize
96
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
2.69
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
14.11
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
70.79
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.64
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
-0.6
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
24.38
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1.76
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
4.31
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
2
Number of binary attributes.
MeanMutualInformation
0.2
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
7.94
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
5.9
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
-1.94
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
9.07
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.47
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.18
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
9.49
Minimum of means among attributes of the numeric type.
MinMutualInformation
0.03
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
-3.63
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
1.92
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
11.03
Percentage of instances belonging to the least frequent class.
MinorityClassSize
44
Number of instances belonging to the least frequent class.
Show all 62 properties

21 tasks

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