Data
BNG(waveform-5000)

BNG(waveform-5000)

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

class (target)nominal3 unique values
0 missing
x1numeric865038 unique values
0 missing
x2numeric868812 unique values
0 missing
x3numeric883965 unique values
0 missing
x4numeric903628 unique values
0 missing
x5numeric916276 unique values
0 missing
x6numeric924219 unique values
0 missing
x7numeric931175 unique values
0 missing
x8numeric920811 unique values
0 missing
x9numeric916348 unique values
0 missing
x10numeric909976 unique values
0 missing
x11numeric917054 unique values
0 missing
x12numeric910595 unique values
0 missing
x13numeric916269 unique values
0 missing
x14numeric921335 unique values
0 missing
x15numeric929206 unique values
0 missing
x16numeric922251 unique values
0 missing
x17numeric915549 unique values
0 missing
x18numeric902688 unique values
0 missing
x19numeric886257 unique values
0 missing
x20numeric872299 unique values
0 missing
x21numeric864486 unique values
0 missing
x22numeric864920 unique values
0 missing
x23numeric862230 unique values
0 missing
x24numeric865816 unique values
0 missing
x25numeric865203 unique values
0 missing
x26numeric862034 unique values
0 missing
x27numeric861614 unique values
0 missing
x28numeric864442 unique values
0 missing
x29numeric861801 unique values
0 missing
x30numeric860781 unique values
0 missing
x31numeric863116 unique values
0 missing
x32numeric863060 unique values
0 missing
x33numeric866431 unique values
0 missing
x34numeric865170 unique values
0 missing
x35numeric864302 unique values
0 missing
x36numeric863212 unique values
0 missing
x37numeric864709 unique values
0 missing
x38numeric862869 unique values
0 missing
x39numeric864827 unique values
0 missing
x40numeric864203 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
41
Number of attributes (columns) of the dataset.
3
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.
40
Number of numeric attributes.
1
Number of nominal attributes.
0.01
Second quartile (Median) of skewness among attributes of the numeric type.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
3.36
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.
1.01
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.86
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.
3
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.
0.19
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.
3
The maximum number of distinct values among attributes of the nominal type.
-0.27
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
-0.31
Third quartile of kurtosis among attributes of the numeric type.
0.33
Average class difference between consecutive instances.
0.71
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.27
Maximum skewness among attributes of the numeric type.
0.98
Minimum standard deviation of attributes of the numeric type.
97.56
Percentage of numeric attributes.
1.98
Third quartile of means among attributes of the numeric type.
0.89
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
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.15
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.02
Maximum standard deviation of attributes of the numeric type.
33.06
Percentage of instances belonging to the least frequent class.
2.44
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.15
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
330606
Number of instances belonging to the least frequent class.
First quartile of entropy among attributes.
0.08
Third quartile of skewness among attributes of the numeric type.
0.77
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
0.71
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
-0.44
Mean kurtosis among attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.6
First quartile of kurtosis among attributes of the numeric type.
1.65
Third quartile of standard deviation of attributes of the numeric type.
0.89
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
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.15
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.9
Mean of means among attributes of the numeric type.
0.15
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0
First quartile of means among attributes of the numeric type.
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.15
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of mutual information between the nominal attributes and the target attribute.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.77
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
0.71
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.89
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.
0
Number of binary attributes.
-0.02
First quartile of skewness among attributes of the numeric type.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.89
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.
0.15
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
3
Average number of distinct values among the attributes of the nominal type.
1
First quartile of standard deviation of attributes of the numeric type.
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.15
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
0.84
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.77
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.03
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.77
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
0.21
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
33.84
Percentage of instances belonging to the most frequent class.
1.27
Mean standard deviation of attributes of the numeric type.
-0.35
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
1.58
Entropy of the target attribute values.
0.69
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
338402
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.03
Second quartile (Median) of means among attributes of the numeric type.
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.76
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.45
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
-0.23
Maximum kurtosis among attributes of the numeric type.
-0.02
Minimum of means among attributes of the numeric type.

25 tasks

19 runs - estimation_procedure: 10-fold Crossvalidation - 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: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - 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: 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
288 runs - estimation_procedure: Interleaved Test then Train - 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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