Data
gas-drift

gas-drift

active ARFF Publicly available Visibility: public Uploaded 22-05-2015 by Rafael Gomes Mantovani
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129 features

Class (target)nominal6 unique values
0 missing
V1numeric13904 unique values
0 missing
V2numeric13890 unique values
0 missing
V3numeric13904 unique values
0 missing
V4numeric13905 unique values
0 missing
V5numeric13904 unique values
0 missing
V6numeric13897 unique values
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V7numeric13895 unique values
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V8numeric13907 unique values
0 missing
V9numeric13897 unique values
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V10numeric13888 unique values
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V11numeric13905 unique values
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V12numeric13909 unique values
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V13numeric13906 unique values
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V14numeric13906 unique values
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V15numeric13902 unique values
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V16numeric13908 unique values
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V17numeric13910 unique values
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V18numeric13892 unique values
0 missing
V19numeric13896 unique values
0 missing
V20numeric13903 unique values
0 missing
V21numeric13909 unique values
0 missing
V22numeric13883 unique values
0 missing
V23numeric13903 unique values
0 missing
V24numeric13899 unique values
0 missing
V25numeric13896 unique values
0 missing
V26numeric13885 unique values
0 missing
V27numeric13891 unique values
0 missing
V28numeric13892 unique values
0 missing
V29numeric13893 unique values
0 missing
V30numeric13872 unique values
0 missing
V31numeric13886 unique values
0 missing
V32numeric13891 unique values
0 missing
V33numeric13904 unique values
0 missing
V34numeric13874 unique values
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V35numeric13855 unique values
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0 missing
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0 missing
V40numeric13891 unique values
0 missing
V41numeric13908 unique values
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V42numeric13877 unique values
0 missing
V43numeric13864 unique values
0 missing
V44numeric13891 unique values
0 missing
V45numeric13894 unique values
0 missing
V46numeric13820 unique values
0 missing
V47numeric13859 unique values
0 missing
V48numeric13882 unique values
0 missing
V49numeric13908 unique values
0 missing
V50numeric13898 unique values
0 missing
V51numeric13906 unique values
0 missing
V52numeric13908 unique values
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V53numeric13907 unique values
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V64numeric13904 unique values
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0 missing
V66numeric13889 unique values
0 missing
V67numeric13902 unique values
0 missing
V68numeric13906 unique values
0 missing
V69numeric13907 unique values
0 missing
V70numeric13891 unique values
0 missing
V71numeric13907 unique values
0 missing
V72numeric13906 unique values
0 missing
V73numeric13904 unique values
0 missing
V74numeric13887 unique values
0 missing
V75numeric13904 unique values
0 missing
V76numeric13903 unique values
0 missing
V77numeric13905 unique values
0 missing
V78numeric13897 unique values
0 missing
V79numeric13898 unique values
0 missing
V80numeric13900 unique values
0 missing
V81numeric13908 unique values
0 missing
V82numeric13888 unique values
0 missing
V83numeric13906 unique values
0 missing
V84numeric13906 unique values
0 missing
V85numeric13905 unique values
0 missing
V86numeric13892 unique values
0 missing
V87numeric13899 unique values
0 missing
V88numeric13903 unique values
0 missing
V89numeric13908 unique values
0 missing
V90numeric13900 unique values
0 missing
V91numeric13903 unique values
0 missing
V92numeric13905 unique values
0 missing
V93numeric13903 unique values
0 missing
V94numeric13886 unique values
0 missing
V95numeric13896 unique values
0 missing
V96numeric13902 unique values
0 missing
V97numeric13902 unique values
0 missing
V98numeric13882 unique values
0 missing
V99numeric13872 unique values
0 missing
V100numeric13905 unique values
0 missing
V101numeric13902 unique values
0 missing
V102numeric13854 unique values
0 missing
V103numeric13882 unique values
0 missing
V104numeric13895 unique values
0 missing
V105numeric13910 unique values
0 missing
V106numeric13885 unique values
0 missing
V107numeric13876 unique values
0 missing
V108numeric13894 unique values
0 missing
V109numeric13895 unique values
0 missing
V110numeric13850 unique values
0 missing
V111numeric13875 unique values
0 missing
V112numeric13875 unique values
0 missing
V113numeric13905 unique values
0 missing
V114numeric13898 unique values
0 missing
V115numeric13903 unique values
0 missing
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0 missing
V117numeric13906 unique values
0 missing
V118numeric13898 unique values
0 missing
V119numeric13903 unique values
0 missing
V120numeric13907 unique values
0 missing
V121numeric13909 unique values
0 missing
V122numeric13898 unique values
0 missing
V123numeric13903 unique values
0 missing
V124numeric13907 unique values
0 missing
V125numeric13903 unique values
0 missing
V126numeric13898 unique values
0 missing
V127numeric13905 unique values
0 missing
V128numeric13907 unique values
0 missing

107 properties

13910
Number of instances (rows) of the dataset.
129
Number of attributes (columns) of the dataset.
6
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.
128
Number of numeric attributes.
1
Number of nominal attributes.
Second quartile (Median) of entropy among attributes.
0.04
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.94
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
0.01
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
21.63
Percentage of instances belonging to the most frequent class.
2729.31
Mean standard deviation of attributes of the numeric type.
10.32
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
2.55
Entropy of the target attribute values.
0.99
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
3009
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
5.37
Second quartile (Median) of means among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.07
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.04
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.61
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
13909.09
Maximum kurtosis among attributes of the numeric type.
-72.75
Minimum of means among attributes of the numeric type.
1.3
Second quartile (Median) of skewness among attributes of the numeric type.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
57340.1
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
9.63
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.01
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
6
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.04
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.
6
The maximum number of distinct values among attributes of the nominal type.
-87.65
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
80.89
Third quartile of kurtosis among attributes of the numeric type.
0.59
Average class difference between consecutive instances.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
117.93
Maximum skewness among attributes of the numeric type.
0.53
Minimum standard deviation of attributes of the numeric type.
99.22
Percentage of numeric attributes.
15.19
Third quartile of means among attributes of the numeric type.
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
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.03
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
69844.79
Maximum standard deviation of attributes of the numeric type.
11.8
Percentage of instances belonging to the least frequent class.
0.78
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.05
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
0.04
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
1641
Number of instances belonging to the least frequent class.
First quartile of entropy among attributes.
2.54
Third quartile of skewness among attributes of the numeric type.
0.94
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
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1037.15
Mean kurtosis among attributes of the numeric type.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.43
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
4.23
First quartile of kurtosis among attributes of the numeric type.
24.79
Third quartile of standard deviation of attributes of the numeric type.
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
0.98
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.03
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
2791.46
Mean of means among attributes of the numeric type.
0.49
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-4.77
First quartile of means among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.05
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
0.04
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.04
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.94
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
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.98
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.
-2.29
First quartile of skewness among attributes of the numeric type.
0.95
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.03
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
6
Average number of distinct values among the attributes of the nominal type.
4.36
First quartile of standard deviation of attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.05
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
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.96
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
4.62
Mean skewness among attributes of the numeric type.

11 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: Leave one out - target_feature: Class
0 runs - estimation_procedure: 10% Holdout set - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - target_feature: Class
0 runs - estimation_procedure: 20% Holdout (Ordered) - target_feature: Class
0 runs - estimation_procedure: Test on Training Data - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: 10 times 10-fold Learning Curve - target_feature: Class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
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