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cleve

cleve

active ARFF public Visibility: public Uploaded 06-04-2017 by Arnold
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cleve-pmlb

14 features

class (target)nominal2 unique values
0 missing
Agenumeric41 unique values
0 missing
Sexnominal2 unique values
0 missing
Chest_pain_typenominal4 unique values
0 missing
Trestbpsnumeric49 unique values
0 missing
Cholesterolnumeric152 unique values
0 missing
Fasting_blood_sugar_<_120nominal2 unique values
0 missing
Resting_ecgnominal3 unique values
0 missing
Max_heart_ratenumeric91 unique values
0 missing
Exercise_induced_anginanominal2 unique values
0 missing
Oldpeaknumeric40 unique values
0 missing
Slopenominal3 unique values
0 missing
Number_of_vessels_colorednominal5 unique values
0 missing
Thalnominal4 unique values
0 missing
Show all 14 features

62 properties

NumberOfInstances
303
Number of instances (rows) of the dataset.
NumberOfFeatures
14
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
5
Number of numeric attributes.
NumberOfSymbolicFeatures
9
Number of nominal attributes.
Quartile1MutualInformation
0.03
First quartile of mutual information between the nominal attributes and the target attribute.
PercentageOfBinaryFeatures
28.57
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
35.71
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
64.29
Percentage of nominal attributes.
Quartile1AttributeEntropy
0.9
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.3
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
27.7
First quartile of means among attributes of the numeric type.
StdvNominalAttDistinctValues
1.12
Standard deviation of the number of distinct values among attributes of the nominal type.
Quartile1SkewnessOfNumericAtts
-0.37
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
5.12
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
1.19
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
0.93
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
131.62
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
0.13
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
0.71
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
17.54
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
1.57
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
3.04
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
197.96
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
0.2
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
1.21
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
37.37
Third quartile of standard deviation of attributes of the numeric type.
AutoCorrelation
0.94
Average class difference between consecutive instances.
MeanMeansOfNumericAtts
116.59
Mean of means among attributes of the numeric type.
ClassEntropy
0.99
Entropy of the target attribute values.
Dimensionality
0.05
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
8.4
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
MajorityClassPercentage
54.46
Percentage of instances belonging to the most frequent class.
MajorityClassSize
165
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
1.74
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
4.51
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
246.26
Maximum of means among attributes of the numeric type.
MaxMutualInformation
0.21
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
5
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
1.27
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
51.83
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
1.19
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
1.28
Mean kurtosis among attributes of the numeric type.
NumberOfBinaryFeatures
4
Number of binary attributes.
MeanMutualInformation
0.12
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
9.04
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
3
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
0.48
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
20.5
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
0.61
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.54
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
1.04
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
-0.54
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
1.16
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
45.54
Percentage of instances belonging to the least frequent class.
MinorityClassSize
138
Number of instances belonging to the least frequent class.
Show all 62 properties

21 tasks

Supervised Classification on cleve
32 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Learning Curve on cleve
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on cleve
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on cleve
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on cleve
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on cleve
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on cleve
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on cleve
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on cleve
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on cleve
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
Clustering on cleve
0 runs
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
Clustering on cleve
0 runs - estimation_procedure: 50 times Clustering
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