Data
meta_stream_intervals.arff

meta_stream_intervals.arff

active ARFF Publicly available Visibility: public Uploaded 13-05-2014 by Jan van Rijn
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
  • Computational Techniques Data Science study_1 study_41
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit

75 features

class (target)nominal11 unique values
0 missing
openml_task_idnumeric49 unique values
0 missing
openml_interval_startnumeric1455 unique values
0 missing
openml_interval_endnumeric1455 unique values
0 missing
openml_classifier_moa.WEKAClassifier_J48(1)numeric32271 unique values
0 missing
openml_classifier_moa.LeveragingBag_HoeffdingTree(1)numeric36462 unique values
0 missing
openml_classifier_moa.WEKAClassifier_SMO_PolyKernel(1)numeric34333 unique values
0 missing
openml_classifier_moa.kNN(1)numeric28094 unique values
0 missing
openml_classifier_moa.WEKAClassifier_OneR(1)numeric32658 unique values
0 missing
openml_classifier_moa.LeveragingBag_kNN(1)numeric27780 unique values
0 missing
openml_classifier_moa.OzaBoost_HoeffdingTree(1)numeric39140 unique values
0 missing
openml_classifier_moa.HoeffdingTree(1)numeric39756 unique values
0 missing
openml_classifier_moa.SGD(1)numeric33477 unique values
0 missing
openml_classifier_moa.NaiveBayes(1)numeric30876 unique values
0 missing
openml_classifier_moa.WEKAClassifier_REPTree(1)numeric33602 unique values
0 missing
openml_classifier_moa.OzaBag_HoeffdingTree(1)numeric39043 unique values
0 missing
openml_classifier_moa.SPegasos(1)numeric37902 unique values
0 missing
meta_REPTreeDepth2ErrRatenumeric831 unique values
0 missing
meta_J48.00001.ErrRatenumeric762 unique values
0 missing
meta_NBErrRatenumeric731 unique values
0 missing
meta_MeanMutualInformationnumeric24191 unique values
0 missing
meta_NBAUCnumeric40124 unique values
0 missing
meta_DecisionStumpKappanumeric38448 unique values
0 missing
meta_HoeffdingDDM.warningsnumeric31 unique values
0 missing
meta_NoiseToSignalRationumeric27159 unique values
0 missing
meta_RandomTreeDepth3AUC_K=0numeric41781 unique values
0 missing
meta_PercentageOfNumericAttsnumeric27 unique values
0 missing
meta_EquivalentNumberOfAttsnumeric27169 unique values
0 missing
meta_HoeffdingDDM.changesnumeric20 unique values
0 missing
meta_ClassEntropynumeric15806 unique values
0 missing
meta_NaiveBayesDdm.changesnumeric21 unique values
0 missing
meta_NumNominalAttsnumeric25 unique values
0 missing
meta_REPTreeDepth3AUCnumeric40035 unique values
0 missing
meta_MeanAttributeEntropynumeric15634 unique values
0 missing
meta_MeanKurtosisOfNumericAttsnumeric30695 unique values
0 missing
meta_REPTreeDepth3Kappanumeric41090 unique values
0 missing
meta_J48.001.ErrRatenumeric753 unique values
0 missing
meta_NumNumericAttsnumeric20 unique values
0 missing
meta_ClassCountnumeric10 unique values
0 missing
meta_J48.00001.AUCnumeric38779 unique values
0 missing
meta_PercentageOfBinaryAttsnumeric23 unique values
0 missing
meta_DecisionStumpAUCnumeric40510 unique values
0 missing
meta_RandomTreeDepth1AUC_K=0numeric41486 unique values
0 missing
meta_REPTreeDepth2Kappanumeric40525 unique values
0 missing
meta_PositivePercentagenumeric458 unique values
0 missing
meta_J48.0001.ErrRatenumeric759 unique values
0 missing
meta_MinNominalAttDistinctValuesnumeric6 unique values
0 missing
meta_RandomTreeDepth2AUC_K=0numeric41883 unique values
0 missing
meta_MeanMeansOfNumericAttsnumeric29817 unique values
0 missing
meta_J48.0001.kappanumeric39647 unique values
0 missing
meta_MeanNominalAttDistinctValuesnumeric27 unique values
0 missing
meta_J48.00001.kappanumeric39520 unique values
0 missing
meta_PercentageOfNominalAttsnumeric30 unique values
0 missing
meta_REPTreeDepth1Kappanumeric37613 unique values
0 missing
meta_NegativePercentagenumeric774 unique values
0 missing
meta_NumBinaryAttsnumeric15 unique values
0 missing
meta_NaiveBayesDdm.warningsnumeric37 unique values
0 missing
meta_MaxNominalAttDistinctValuesnumeric15 unique values
0 missing
meta_J48.001.AUCnumeric38908 unique values
0 missing
meta_J48.0001.AUCnumeric38832 unique values
0 missing
meta_NBKappanumeric42417 unique values
0 missing
meta_REPTreeDepth1AUCnumeric37613 unique values
0 missing
meta_NaiveBayesAdwin.changesnumeric12 unique values
0 missing
meta_REPTreeDepth3ErrRatenumeric763 unique values
0 missing
meta_DecisionStumpErrRatenumeric887 unique values
0 missing
meta_MeanStdDevOfNumericAttsnumeric29435 unique values
0 missing
meta_Dimensionalitynumeric27 unique values
0 missing
meta_REPTreeDepth2AUCnumeric39901 unique values
0 missing
meta_StdvNominalAttDistinctValuesnumeric24 unique values
0 missing
meta_HoeffdingAdwin.changesnumeric13 unique values
0 missing
meta_MeanSkewnessOfNumericAttsnumeric30152 unique values
0 missing
meta_DefaultAccuracynumeric774 unique values
0 missing
meta_REPTreeDepth1ErrRatenumeric909 unique values
0 missing
meta_J48.001.kappanumeric39745 unique values
0 missing
meta_NumAttributesnumeric27 unique values
0 missing

107 properties

45164
Number of instances (rows) of the dataset.
75
Number of attributes (columns) of the dataset.
11
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
74
Number of numeric attributes.
1
Number of nominal attributes.
297091.48
Maximum standard deviation of attributes of the numeric type.
0.16
Percentage of instances belonging to the least frequent class.
98.67
Percentage of numeric attributes.
4.3
Third quartile of means among attributes of the numeric type.
0.99
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
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
73
Number of instances belonging to the least frequent class.
1.33
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
52.63
Mean kurtosis among attributes of the numeric type.
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
1.09
Third quartile of skewness among attributes of the numeric type.
0.97
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
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
13539.85
Mean of means among attributes of the numeric type.
0.43
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.78
First quartile of kurtosis among attributes of the numeric type.
12.51
Third quartile of standard deviation of attributes of the numeric type.
0.99
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
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.47
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.47
First quartile of means among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.97
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
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
11
Average number of distinct values among the attributes of the nominal type.
-0.67
First quartile of skewness among attributes of the numeric type.
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.99
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.77
Mean skewness among attributes of the numeric type.
0.18
First quartile of standard deviation of attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
8054.88
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.97
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
0.04
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
50.97
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.24
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2.33
Entropy of the target attribute values.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
23021
Number of instances belonging to the most frequent class.
-1.95
Minimum kurtosis among attributes of the numeric type.
0.74
Second quartile (Median) of means among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-25.8
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.01
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.49
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
2963.56
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.16
Second quartile (Median) of skewness among attributes of the numeric type.
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
500704.9
Maximum of means among attributes of the numeric type.
11
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
0.36
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
-10.62
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
11
The maximum number of distinct values among attributes of the nominal type.
0.02
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
2.95
Third quartile of kurtosis among attributes of the numeric type.
0.31
Average class difference between consecutive instances.
0.98
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
36.62
Maximum skewness among attributes of the numeric type.

25 tasks

138 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
119 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
105 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
43 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task