Data
oil_spill

oil_spill

active ARFF Publicly available Visibility: public Uploaded 25-08-2014 by Tobias Kuehn
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Author: Source: Unknown - Please cite: Oil dataset Past Usage: 1. Kubat, M., Holte, R.,

50 features

class (target)nominal2 unique values
0 missing
attr1numeric238 unique values
0 missing
attr2numeric297 unique values
0 missing
attr3numeric927 unique values
0 missing
attr4numeric933 unique values
0 missing
attr5numeric179 unique values
0 missing
attr6numeric375 unique values
0 missing
attr7numeric820 unique values
0 missing
attr8numeric618 unique values
0 missing
attr9numeric561 unique values
0 missing
attr10numeric57 unique values
0 missing
attr11numeric577 unique values
0 missing
attr12numeric59 unique values
0 missing
attr13numeric73 unique values
0 missing
attr14numeric107 unique values
0 missing
attr15numeric53 unique values
0 missing
attr16numeric91 unique values
0 missing
attr17numeric893 unique values
0 missing
attr18numeric810 unique values
0 missing
attr19numeric170 unique values
0 missing
attr20numeric53 unique values
0 missing
attr21numeric68 unique values
0 missing
attr22numeric9 unique values
0 missing
attr23numeric1 unique values
0 missing
attr24numeric92 unique values
0 missing
attr25numeric9 unique values
0 missing
attr26numeric8 unique values
0 missing
attr27numeric9 unique values
0 missing
attr28numeric308 unique values
0 missing
attr29numeric447 unique values
0 missing
attr30numeric392 unique values
0 missing
attr31numeric107 unique values
0 missing
attr32numeric42 unique values
0 missing
attr33numeric4 unique values
0 missing
attr34numeric45 unique values
0 missing
attr35numeric141 unique values
0 missing
attr36numeric110 unique values
0 missing
attr37numeric3 unique values
0 missing
attr38numeric758 unique values
0 missing
attr39numeric9 unique values
0 missing
attr40numeric9 unique values
0 missing
attr41numeric388 unique values
0 missing
attr42numeric220 unique values
0 missing
attr43numeric644 unique values
0 missing
attr44numeric649 unique values
0 missing
attr45numeric499 unique values
0 missing
attr46numeric2 unique values
0 missing
attr47numeric937 unique values
0 missing
attr48numeric169 unique values
0 missing
attr49numeric286 unique values
0 missing

107 properties

937
Number of instances (rows) of the dataset.
50
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.
49
Number of numeric attributes.
1
Number of nominal attributes.
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.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.33
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
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.
0.57
First quartile of skewness among attributes of the numeric type.
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.74
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.
0.07
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
3.85
Mean skewness among attributes of the numeric type.
0.26
First quartile of standard deviation of attributes of the numeric type.
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.04
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
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
78741.02
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.33
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
95.62
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
2.96
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.26
Entropy of the target attribute values.
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
896
Number of instances belonging to the most frequent class.
-1.44
Minimum kurtosis among attributes of the numeric type.
9.13
Second quartile (Median) of means among attributes of the numeric type.
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-2.83
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.05
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
535.5
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
1.47
Second quartile (Median) of skewness among attributes of the numeric type.
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
769696.38
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
2
Percentage of binary attributes.
5.03
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.05
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
-2.02
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.07
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.
0
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
52.54
Third quartile of kurtosis among attributes of the numeric type.
0.93
Average class difference between consecutive instances.
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
21.51
Maximum skewness among attributes of the numeric type.
4.38
Percentage of instances belonging to the least frequent class.
98
Percentage of numeric attributes.
108
Third quartile of means among attributes of the numeric type.
0.74
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
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.07
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3831151.03
Maximum standard deviation of attributes of the numeric type.
41
Number of instances belonging to the least frequent class.
2
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.04
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
0.07
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
5.79
Third quartile of skewness among attributes of the numeric type.
0.33
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
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
51.71
Mean kurtosis among attributes of the numeric type.
0.32
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.08
First quartile of kurtosis among attributes of the numeric type.
228.51
Third quartile of standard deviation of attributes of the numeric type.
0.74
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
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.07
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
16103.51
Mean of means among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.31
First quartile of means among attributes of the numeric type.
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.04
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
0.07
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

12 tasks

169 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - 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: Interleaved Test then Train - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
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