Data
BNG(sonar)

BNG(sonar)

active ARFF Publicly available Visibility: public Uploaded 29-04-2014 by Jan van Rijn
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61 features

Class (target)nominal2 unique values
0 missing
attribute_1numeric108158 unique values
0 missing
attribute_2numeric139333 unique values
0 missing
attribute_3numeric153788 unique values
0 missing
attribute_4numeric172749 unique values
0 missing
attribute_5numeric201409 unique values
0 missing
attribute_6numeric230774 unique values
0 missing
attribute_7numeric247606 unique values
0 missing
attribute_8numeric291785 unique values
0 missing
attribute_9numeric347510 unique values
0 missing
attribute_10numeric380595 unique values
0 missing
attribute_11numeric387419 unique values
0 missing
attribute_12numeric413481 unique values
0 missing
attribute_13numeric428985 unique values
0 missing
attribute_14numeric447215 unique values
0 missing
attribute_15numeric513996 unique values
0 missing
attribute_16numeric527801 unique values
0 missing
attribute_17numeric552886 unique values
0 missing
attribute_18numeric554510 unique values
0 missing
attribute_19numeric577363 unique values
0 missing
attribute_20numeric591874 unique values
0 missing
attribute_21numeric596052 unique values
0 missing
attribute_22numeric589369 unique values
0 missing
attribute_23numeric579140 unique values
0 missing
attribute_24numeric558332 unique values
0 missing
attribute_25numeric558280 unique values
0 missing
attribute_26numeric545626 unique values
0 missing
attribute_27numeric542419 unique values
0 missing
attribute_28numeric548628 unique values
0 missing
attribute_29numeric564620 unique values
0 missing
attribute_30numeric569868 unique values
0 missing
attribute_31numeric559741 unique values
0 missing
attribute_32numeric554899 unique values
0 missing
attribute_33numeric544001 unique values
0 missing
attribute_34numeric566740 unique values
0 missing
attribute_35numeric579656 unique values
0 missing
attribute_36numeric579415 unique values
0 missing
attribute_37numeric546629 unique values
0 missing
attribute_38numeric503954 unique values
0 missing
attribute_39numeric505016 unique values
0 missing
attribute_40numeric488044 unique values
0 missing
attribute_41numeric465907 unique values
0 missing
attribute_42numeric468772 unique values
0 missing
attribute_43numeric418686 unique values
0 missing
attribute_44numeric381727 unique values
0 missing
attribute_45numeric375891 unique values
0 missing
attribute_46numeric346046 unique values
0 missing
attribute_47numeric275538 unique values
0 missing
attribute_48numeric230947 unique values
0 missing
attribute_49numeric148555 unique values
0 missing
attribute_50numeric70707 unique values
0 missing
attribute_51numeric65880 unique values
0 missing
attribute_52numeric51978 unique values
0 missing
attribute_53numeric34855 unique values
0 missing
attribute_54numeric36649 unique values
0 missing
attribute_55numeric37860 unique values
0 missing
attribute_56numeric31960 unique values
0 missing
attribute_57numeric31039 unique values
0 missing
attribute_58numeric35444 unique values
0 missing
attribute_59numeric33907 unique values
0 missing
attribute_60numeric30173 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
61
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.
60
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.
0.18
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.62
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
0.78
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.
0.45
First quartile of skewness among attributes of the numeric type.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.82
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.
0.2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.82
Mean skewness among attributes of the numeric type.
0.04
First quartile of standard deviation of attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.19
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
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.14
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.18
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.62
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
0.24
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
53.25
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.45
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
1
Entropy of the target attribute values.
0.52
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
532538
Number of instances belonging to the most frequent class.
-1.17
Minimum kurtosis among attributes of the numeric type.
0.26
Second quartile (Median) of means among attributes of the numeric type.
0.89
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.
0.01
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.18
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.29
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
4.91
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.88
Second quartile (Median) of skewness among attributes of the numeric type.
0.65
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.42
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0.71
Maximum of means among attributes of the numeric type.
2
The minimal number of distinct values among attributes of the nominal type.
1.64
Percentage of binary attributes.
0.14
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.77
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.
-0.79
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.23
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.
0.01
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
1.9
Third quartile of kurtosis among attributes of the numeric type.
0.5
Average class difference between consecutive instances.
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.08
Maximum skewness among attributes of the numeric type.
46.75
Percentage of instances belonging to the least frequent class.
98.36
Percentage of numeric attributes.
0.43
Third quartile of means among attributes of the numeric type.
0.82
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
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.26
Maximum standard deviation of attributes of the numeric type.
467462
Number of instances belonging to the least frequent class.
1.64
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.19
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
0.23
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
1.45
Third quartile of skewness among attributes of the numeric type.
0.62
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
0.53
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.79
Mean kurtosis among attributes of the numeric type.
0.25
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.6
First quartile of kurtosis among attributes of the numeric type.
0.24
Third quartile of standard deviation of attributes of the numeric type.
0.82
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
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.28
Mean of means among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
0.51
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.05
First quartile of means among attributes of the numeric type.
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.19
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
0.23
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.61
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

8 tasks

6 runs - estimation_procedure: 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 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Class
290 runs - estimation_procedure: Interleaved Test then Train - target_feature: Class
Define a new task