DEVELOPMENT... OpenML
Data
cardiotocography

cardiotocography

active ARFF Publicly available Visibility: public Uploaded 01-06-2015 by unknown
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
  • derived study_50 study_7 study_236
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Author: J. P. Marques de Sá, J. Bernardes, D. Ayers de Campos. Source: [original](http://www.openml.org/d/1466) - UCI Please cite: A 3-class version of Cardiotocography dataset.

36 features

Class (target)nominal3 unique values
0 missing
V20numeric9 unique values
0 missing
V19numeric18 unique values
0 missing
V21numeric88 unique values
0 missing
V22numeric103 unique values
0 missing
V23numeric95 unique values
0 missing
V24numeric133 unique values
0 missing
V25numeric3 unique values
0 missing
V26numeric2 unique values
0 missing
V27numeric2 unique values
0 missing
V28numeric2 unique values
0 missing
V29numeric2 unique values
0 missing
V30numeric2 unique values
0 missing
V31numeric2 unique values
0 missing
V32numeric2 unique values
0 missing
V33numeric2 unique values
0 missing
V34numeric2 unique values
0 missing
V35numeric2 unique values
0 missing
V10numeric57 unique values
0 missing
V2numeric979 unique values
0 missing
V3numeric1064 unique values
0 missing
V4numeric48 unique values
0 missing
V5numeric48 unique values
0 missing
V6numeric22 unique values
0 missing
V7numeric96 unique values
0 missing
V8numeric19 unique values
0 missing
V9numeric75 unique values
0 missing
V1numeric48 unique values
0 missing
V11numeric87 unique values
0 missing
V12numeric249 unique values
0 missing
V13numeric15 unique values
0 missing
V14numeric2 unique values
0 missing
V15numeric5 unique values
0 missing
V16numeric154 unique values
0 missing
V17numeric109 unique values
0 missing
V18numeric86 unique values
0 missing
Show all 36 features

107 properties

NumberOfInstances
2126
Number of instances (rows) of the dataset.
NumberOfFeatures
36
Number of attributes (columns) of the dataset.
NumberOfClasses
3
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
35
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.87
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_DecisionStumpErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_DecisionStumpKappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_NaiveBayesAUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_NaiveBayesErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_NaiveBayesKappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_kNN1NAUC
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_kNN1NErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
CfsSubsetEval_kNN1NKappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
ClassEntropy
0.97
Entropy of the target attribute values.
DecisionStumpAUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.02
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.
J48.00001.AUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
77.85
Percentage of instances belonging to the most frequent class.
MajorityClassSize
1655
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
299.42
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
1702.88
Maximum of means among attributes of the numeric type.
MaxMutualInformation
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
17.35
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
930.92
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
17.74
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
106.21
Mean of means among attributes of the numeric type.
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
3
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
2.39
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
60.5
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.37
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
3
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-1
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.06
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
8.28
Percentage of instances belonging to the least frequent class.
MinorityClassSize
176
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.1
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.76
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
97.22
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
2.78
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.29
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.13
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
0.12
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.36
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
3.01
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
3.66
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
1.66
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
2.95
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
15.13
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
93.58
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
3.92
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
17.19
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.03
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.03
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.03
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.91
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.01
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.97
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

14 tasks

Supervised Classification on cardiotocography
103 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
Supervised Classification on cardiotocography
31 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
Supervised Classification on cardiotocography
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
Clustering on cardiotocography
0 runs
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Clustering on cardiotocography
0 runs - estimation_procedure: 50 times Clustering
Define a new task