Data
BNG(mfeat-karhunen)

BNG(mfeat-karhunen)

active ARFF Publicly available Visibility: public Uploaded 28-04-2014 by Jan van Rijn
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65 features

class (target)nominal10 unique values
0 missing
att1numeric981084 unique values
0 missing
att2numeric974494 unique values
0 missing
att3numeric973019 unique values
0 missing
att4numeric971961 unique values
0 missing
att5numeric963639 unique values
0 missing
att6numeric957480 unique values
0 missing
att7numeric963388 unique values
0 missing
att8numeric957645 unique values
0 missing
att9numeric963536 unique values
0 missing
att10numeric962619 unique values
0 missing
att11numeric957122 unique values
0 missing
att12numeric956134 unique values
0 missing
att13numeric946842 unique values
0 missing
att14numeric944981 unique values
0 missing
att15numeric940578 unique values
0 missing
att16numeric948598 unique values
0 missing
att17numeric940083 unique values
0 missing
att18numeric936885 unique values
0 missing
att19numeric942325 unique values
0 missing
att20numeric937350 unique values
0 missing
att21numeric946577 unique values
0 missing
att22numeric931966 unique values
0 missing
att23numeric940820 unique values
0 missing
att24numeric924124 unique values
0 missing
att25numeric932077 unique values
0 missing
att26numeric930751 unique values
0 missing
att27numeric917935 unique values
0 missing
att28numeric929848 unique values
0 missing
att29numeric905800 unique values
0 missing
att30numeric913167 unique values
0 missing
att31numeric918140 unique values
0 missing
att32numeric913602 unique values
0 missing
att33numeric908729 unique values
0 missing
att34numeric910918 unique values
0 missing
att35numeric906259 unique values
0 missing
att36numeric920014 unique values
0 missing
att37numeric907683 unique values
0 missing
att38numeric912002 unique values
0 missing
att39numeric894097 unique values
0 missing
att40numeric898550 unique values
0 missing
att41numeric885108 unique values
0 missing
att42numeric899239 unique values
0 missing
att43numeric909870 unique values
0 missing
att44numeric901483 unique values
0 missing
att45numeric889867 unique values
0 missing
att46numeric870883 unique values
0 missing
att47numeric878925 unique values
0 missing
att48numeric877038 unique values
0 missing
att49numeric895253 unique values
0 missing
att50numeric873423 unique values
0 missing
att51numeric877916 unique values
0 missing
att52numeric884090 unique values
0 missing
att53numeric868966 unique values
0 missing
att54numeric869374 unique values
0 missing
att55numeric868964 unique values
0 missing
att56numeric882052 unique values
0 missing
att57numeric859869 unique values
0 missing
att58numeric865154 unique values
0 missing
att59numeric853354 unique values
0 missing
att60numeric870590 unique values
0 missing
att61numeric853123 unique values
0 missing
att62numeric850326 unique values
0 missing
att63numeric851654 unique values
0 missing
att64numeric868328 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
65
Number of attributes (columns) of the dataset.
10
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.
64
Number of numeric attributes.
1
Number of nominal attributes.
10
The maximum number of distinct values among attributes of the nominal type.
-0.33
Minimum skewness among attributes of the numeric 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.
0.4
Maximum skewness among attributes of the numeric type.
0.89
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
-0.28
Third quartile of kurtosis among attributes of the numeric type.
0.1
Average class difference between consecutive instances.
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
7.7
Maximum standard deviation of attributes of the numeric type.
9.95
Percentage of instances belonging to the least frequent class.
98.46
Percentage of numeric attributes.
0.32
Third quartile of means among attributes of the numeric type.
0.92
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
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.13
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
99545
Number of instances belonging to the least frequent class.
1.54
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.13
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
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
-0.35
Mean kurtosis among attributes of the numeric type.
1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.05
Third quartile of skewness among attributes of the numeric type.
0.85
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
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.05
Mean of means among attributes of the numeric type.
0.03
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.41
First quartile of kurtosis among attributes of the numeric type.
2.66
Third quartile of standard deviation of attributes of the numeric type.
0.92
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
0.89
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.13
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.97
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.3
First quartile of means among attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.13
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
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
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.
First quartile of mutual information between the nominal attributes and the target attribute.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.85
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
0.79
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
10
Average number of distinct values among the attributes of the nominal type.
-0.1
First quartile of skewness among attributes of the numeric type.
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.92
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.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
-0
Mean skewness among attributes of the numeric type.
1.14
First quartile of standard deviation of attributes of the numeric type.
0.97
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.13
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
0.96
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.85
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.15
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.85
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
0.08
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
10.04
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.33
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.32
Entropy of the target attribute values.
0.92
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
100410
Number of instances belonging to the most frequent class.
-0.96
Minimum kurtosis among attributes of the numeric type.
0.01
Second quartile (Median) of means among attributes of the numeric type.
0.97
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.
-1.83
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.81
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
-0.02
Maximum kurtosis among attributes of the numeric type.
2.9
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
-0.02
Second quartile (Median) of skewness among attributes of the numeric type.
0.86
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum mutual information between the nominal attributes and the target attribute.
10
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
1.65
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.89
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.

13 tasks

6 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
46 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task