DEVELOPMENT... OpenML
Measure
Sort: most recent
226 results
measure
Filter results by:
wall_clock_time_millis
The number of milliseconds from the start of training until the completion of testing. Thus, involves both training and testing. Does not take into account the number of cores.
evaluation measure
wall_clock_time_millis_training
The number of milliseconds from the start of training until the completion of training. Does not take into account the number of cores.
evaluation measure
wall_clock_time_millis_testing
The number of milliseconds from the start of testing until the completion of testing. Does not take into account the number of cores.
evaluation measure
CardinalityAtFour
No data.
data quality
CardinalityAtThree
No data.
data quality
CardinalityAtTwo
No data.
data quality
MaxCardinalityOfNominalAttributes
No data.
data quality
MaxCardinalityOfNumericAttributes
No data.
data quality
MeanCardinalityOfNominalAttributes
No data.
data quality
MinCardinalityOfNominalAttributes
No data.
data quality
MinCardinalityOfNumericAttributes
No data.
data quality
StdevCardinalityOfNominalAttributes
No data.
data quality
MeanCardinalityOfNumericAttributes
No data.
data quality
StdevCardinalityOfNumericAttributes
No data.
data quality
NumberOfInstances
Number of instances (rows) of the dataset.
data quality
AutoCorrelation
Average class difference between consecutive instances.
data quality
CfsSubsetEval_DecisionStumpAUC
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
data quality
CfsSubsetEval_DecisionStumpErrRate
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
data quality
CfsSubsetEval_DecisionStumpKappa
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
data quality
CfsSubsetEval_NaiveBayesAUC
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
data quality
CfsSubsetEval_NaiveBayesErrRate
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
data quality
CfsSubsetEval_NaiveBayesKappa
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
data quality
CfsSubsetEval_kNN1NAUC
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
data quality
CfsSubsetEval_kNN1NErrRate
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
data quality
CfsSubsetEval_kNN1NKappa
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
data quality
ClassEntropy
Entropy of the target attribute values.
data quality
DecisionStumpAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
data quality
DecisionStumpErrRate
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
data quality
DecisionStumpKappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
data quality
DefaultAccuracy
The predictive accuracy obtained by always predicting the majority class.
data quality
Dimensionality
Number of attributes divided by the number of instances.
data quality
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
data quality
J48.00001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
data quality
J48.00001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
data quality
J48.00001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
data quality
J48.0001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
data quality
J48.0001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
data quality
J48.0001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
data quality
J48.001.AUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
data quality
J48.001.ErrRate
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
data quality
J48.001.Kappa
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
data quality
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
data quality
MajorityClassSize
Number of instances belonging to the most frequent class.
data quality
MaxAttributeEntropy
Maximum entropy among attributes.
data quality
MaxKurtosisOfNumericAtts
Maximum kurtosis among attributes of the numeric type.
data quality
MaxMeansOfNumericAtts
Maximum of means among attributes of the numeric type.
data quality
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
data quality
MaxNominalAttDistinctValues
The maximum number of distinct values among attributes of the nominal type.
data quality
MaxSkewnessOfNumericAtts
Maximum skewness among attributes of the numeric type.
data quality
MaxStdDevOfNumericAtts
Maximum standard deviation of attributes of the numeric type.
data quality
MeanAttributeEntropy
Average entropy of the attributes.
data quality
MeanKurtosisOfNumericAtts
Mean kurtosis among attributes of the numeric type.
data quality
MeanMeansOfNumericAtts
Mean of means among attributes of the numeric type.
data quality
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
data quality
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
data quality
MeanNominalAttDistinctValues
Average number of distinct values among the attributes of the nominal type.
data quality
MeanSkewnessOfNumericAtts
Mean skewness among attributes of the numeric type.
data quality
MeanStdDevOfNumericAtts
Mean standard deviation of attributes of the numeric type.
data quality
MinAttributeEntropy
Minimal entropy among attributes.
data quality
MinKurtosisOfNumericAtts
Minimum kurtosis among attributes of the numeric type.
data quality
MinMeansOfNumericAtts
Minimum of means among attributes of the numeric type.
data quality
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
data quality
MinNominalAttDistinctValues
The minimal number of distinct values among attributes of the nominal type.
data quality
MinSkewnessOfNumericAtts
Minimum skewness among attributes of the numeric type.
data quality
MinStdDevOfNumericAtts
Minimum standard deviation of attributes of the numeric type.
data quality
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
data quality
MinorityClassSize
Number of instances belonging to the least frequent class.
data quality
NaiveBayesAUC
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
data quality
NaiveBayesErrRate
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
data quality
NaiveBayesKappa
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
data quality
NumberOfBinaryFeatures
Number of binary attributes.
data quality
NumberOfClasses
Number of distinct values of the target attribute (if it is nominal).
data quality
NumberOfFeatures
Number of attributes (columns) of the dataset.
data quality
NumberOfInstancesWithMissingValues
Number of instances with at least one value missing.
data quality
NumberOfMissingValues
Number of missing values in the dataset.
data quality
NumberOfNumericFeatures
Number of numeric attributes.
data quality
NumberOfSymbolicFeatures
Number of nominal attributes.
data quality
PercentageOfBinaryFeatures
Percentage of binary attributes.
data quality
PercentageOfInstancesWithMissingValues
Percentage of instances having missing values.
data quality
PercentageOfMissingValues
Percentage of missing values.
data quality
PercentageOfNumericFeatures
Percentage of numeric attributes.
data quality
PercentageOfSymbolicFeatures
Percentage of nominal attributes.
data quality
Quartile1AttributeEntropy
First quartile of entropy among attributes.
data quality
Quartile1KurtosisOfNumericAtts
First quartile of kurtosis among attributes of the numeric type.
data quality
Quartile1MeansOfNumericAtts
First quartile of means among attributes of the numeric type.
data quality
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
data quality
Quartile1SkewnessOfNumericAtts
First quartile of skewness among attributes of the numeric type.
data quality
Quartile1StdDevOfNumericAtts
First quartile of standard deviation of attributes of the numeric type.
data quality
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
data quality
Quartile2KurtosisOfNumericAtts
Second quartile (Median) of kurtosis among attributes of the numeric type.
data quality
Quartile2MeansOfNumericAtts
Second quartile (Median) of means among attributes of the numeric type.
data quality
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
data quality
Quartile2SkewnessOfNumericAtts
Second quartile (Median) of skewness among attributes of the numeric type.
data quality
Quartile2StdDevOfNumericAtts
Second quartile (Median) of standard deviation of attributes of the numeric type.
data quality
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
data quality
Quartile3KurtosisOfNumericAtts
Third quartile of kurtosis among attributes of the numeric type.
data quality
Quartile3MeansOfNumericAtts
Third quartile of means among attributes of the numeric type.
data quality
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
data quality
Quartile3SkewnessOfNumericAtts
Third quartile of skewness among attributes of the numeric type.
data quality
Quartile3StdDevOfNumericAtts
Third quartile of standard deviation of attributes of the numeric type.
data quality