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oil_spill

oil_spill

active ARFF Publicly available Visibility: public Uploaded 25-08-2014 by Hailey
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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
attr37numeric3 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
attr25numeric9 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
attr12numeric59 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
attr24numeric92 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
Show all 50 features

107 properties

NumberOfInstances
937
Number of instances (rows) of the dataset.
NumberOfFeatures
50
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
49
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.93
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
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
CfsSubsetEval_DecisionStumpErrRate
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
CfsSubsetEval_DecisionStumpKappa
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
CfsSubsetEval_NaiveBayesAUC
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
CfsSubsetEval_NaiveBayesErrRate
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
CfsSubsetEval_NaiveBayesKappa
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
CfsSubsetEval_kNN1NAUC
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
CfsSubsetEval_kNN1NErrRate
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
CfsSubsetEval_kNN1NKappa
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
ClassEntropy
0.26
Entropy of the target attribute values.
DecisionStumpAUC
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.05
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.05
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.07
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.07
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.58
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.07
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
95.62
Percentage of instances belonging to the most frequent class.
MajorityClassSize
896
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
535.5
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
769696.38
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
2
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
21.51
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
3831151.03
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
51.71
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
16103.51
Mean of means among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
3.85
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
78741.02
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.44
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
-2.83
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
-2.02
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
4.38
Percentage of instances belonging to the least frequent class.
MinorityClassSize
41
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.32
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
2
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
98
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
2
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
-0.08
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.31
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
0.57
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.26
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
2.96
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
9.13
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
1.47
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
5.03
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
52.54
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
108
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
5.79
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
228.51
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.05
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.07
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.07
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.6
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.07
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.04
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

25 tasks

Supervised Classification on oil_spill
173 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on oil_spill
31 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
Supervised Classification on oil_spill
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Classification on oil_spill
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
Learning Curve on oil_spill
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on oil_spill
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on oil_spill
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on oil_spill
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on oil_spill
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on oil_spill
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on oil_spill
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Learning Curve on oil_spill
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
Supervised Data Stream Classification on oil_spill
0 runs - estimation_procedure: Interleaved Test then Train - evaluation_measure: predictive_accuracy - target_feature: class
Supervised Data Stream Classification on oil_spill
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
Clustering on oil_spill
0 runs
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Clustering on oil_spill
0 runs - estimation_procedure: 50 times Clustering
Define a new task