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active ARFF Publicly available Visibility: public Uploaded 02-12-2015 by Guido Santegoeds
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31 features

Class (target)nominal2 unique values
0 missing
Timenumeric13261 unique values
0 missing
V1numeric13796 unique values
0 missing
V2numeric13794 unique values
0 missing
V3numeric13806 unique values
0 missing
V4numeric13796 unique values
0 missing
V5numeric13798 unique values
0 missing
V6numeric13796 unique values
0 missing
V7numeric13791 unique values
0 missing
V8numeric13758 unique values
0 missing
V9numeric13795 unique values
0 missing
V10numeric13768 unique values
0 missing
V11numeric13793 unique values
0 missing
V12numeric13783 unique values
0 missing
V13numeric13793 unique values
0 missing
V14numeric13783 unique values
0 missing
V15numeric13789 unique values
0 missing
V16numeric13786 unique values
0 missing
V17numeric13782 unique values
0 missing
V18numeric13780 unique values
0 missing
V19numeric13787 unique values
0 missing
V20numeric13728 unique values
0 missing
V21numeric13731 unique values
0 missing
V22numeric13789 unique values
0 missing
V23numeric13725 unique values
0 missing
V24numeric13773 unique values
0 missing
V25numeric13765 unique values
0 missing
V26numeric13749 unique values
0 missing
V27numeric13639 unique values
0 missing
V28numeric13558 unique values
0 missing
Amountnumeric5425 unique values
0 missing

107 properties

14240
Number of instances (rows) of the dataset.
31
Number of attributes (columns) of the dataset.
2
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.
30
Number of numeric attributes.
1
Number of nominal attributes.
0
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0
First quartile of means among attributes of the numeric type.
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.68
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
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.8
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
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
-1.85
First quartile of skewness among attributes of the numeric type.
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0
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
0.81
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0.27
Mean skewness among attributes of the numeric type.
0.72
First quartile of standard deviation of attributes of the numeric type.
0
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.68
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
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
99.84
Percentage of instances belonging to the most frequent class.
1592.84
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.02
Entropy of the target attribute values.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
14217
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
14.08
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.29
Minimum kurtosis among attributes of the numeric type.
-0
Second quartile (Median) of means among attributes of the numeric type.
0
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
459.19
Maximum kurtosis among attributes of the numeric type.
-0.01
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.34
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
94536.8
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
-0.26
Second quartile (Median) of skewness among attributes of the numeric type.
0.78
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.
2
The minimal number of distinct values among attributes of the nominal type.
3.23
Percentage of binary attributes.
0.97
Second quartile (Median) of standard deviation of attributes of the numeric type.
0
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.
2
The maximum number of distinct values among attributes of the nominal type.
-7.56
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
11.34
Maximum skewness among attributes of the numeric type.
0.33
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
93.42
Third quartile of kurtosis among attributes of the numeric type.
1
Average class difference between consecutive instances.
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
47496.7
Maximum standard deviation of attributes of the numeric type.
0.16
Percentage of instances belonging to the least frequent class.
96.77
Percentage of numeric attributes.
0
Third quartile of means among attributes of the numeric type.
0.8
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
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.68
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
23
Number of instances belonging to the least frequent class.
3.23
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0
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
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
60.06
Mean kurtosis among attributes of the numeric type.
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.63
Third quartile of skewness among attributes of the numeric type.
0.68
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
0.8
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
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
3154.27
Mean of means among attributes of the numeric type.
0.02
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.54
First quartile of kurtosis among attributes of the numeric type.
1.36
Third quartile of standard deviation of attributes of the numeric type.

15 tasks

43 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: area_under_roc_curve - target_feature: Class - cost matrix: [[0,1],[500,0]]
31 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - 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
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