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BNG(optdigits)

BNG(optdigits)

active ARFF Publicly available Visibility: public Uploaded 08-04-2014 by Jan van Rijn
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65 features

class (target)nominal10 unique values
0 missing
input1nominal1 unique values
0 missing
input2nominal3 unique values
0 missing
input3nominal3 unique values
0 missing
input4nominal3 unique values
0 missing
input5nominal3 unique values
0 missing
input6nominal3 unique values
0 missing
input7nominal3 unique values
0 missing
input8nominal3 unique values
0 missing
input9nominal3 unique values
0 missing
input10nominal3 unique values
0 missing
input11nominal3 unique values
0 missing
input12nominal3 unique values
0 missing
input13nominal3 unique values
0 missing
input14nominal3 unique values
0 missing
input15nominal3 unique values
0 missing
input16nominal3 unique values
0 missing
input17nominal3 unique values
0 missing
input18nominal3 unique values
0 missing
input19nominal3 unique values
0 missing
input20nominal3 unique values
0 missing
input21nominal3 unique values
0 missing
input22nominal3 unique values
0 missing
input23nominal3 unique values
0 missing
input24nominal3 unique values
0 missing
input25nominal3 unique values
0 missing
input26nominal3 unique values
0 missing
input27nominal3 unique values
0 missing
input28nominal3 unique values
0 missing
input29nominal3 unique values
0 missing
input30nominal3 unique values
0 missing
input31nominal3 unique values
0 missing
input32nominal3 unique values
0 missing
input33nominal3 unique values
0 missing
input34nominal3 unique values
0 missing
input35nominal3 unique values
0 missing
input36nominal3 unique values
0 missing
input37nominal3 unique values
0 missing
input38nominal3 unique values
0 missing
input39nominal3 unique values
0 missing
input40nominal1 unique values
0 missing
input41nominal3 unique values
0 missing
input42nominal3 unique values
0 missing
input43nominal3 unique values
0 missing
input44nominal3 unique values
0 missing
input45nominal3 unique values
0 missing
input46nominal3 unique values
0 missing
input47nominal3 unique values
0 missing
input48nominal3 unique values
0 missing
input49nominal3 unique values
0 missing
input50nominal3 unique values
0 missing
input51nominal3 unique values
0 missing
input52nominal3 unique values
0 missing
input53nominal3 unique values
0 missing
input54nominal3 unique values
0 missing
input55nominal3 unique values
0 missing
input56nominal3 unique values
0 missing
input57nominal3 unique values
0 missing
input58nominal3 unique values
0 missing
input59nominal3 unique values
0 missing
input60nominal3 unique values
0 missing
input61nominal3 unique values
0 missing
input62nominal3 unique values
0 missing
input63nominal3 unique values
0 missing
input64nominal3 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.
0
Number of numeric attributes.
65
Number of nominal attributes.
1.17
Second quartile (Median) of entropy among attributes.
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.88
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
0.05
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
10.17
Percentage of instances belonging to the most frequent class.
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
3.32
Entropy of the target attribute values.
0.94
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
101675
Number of instances belonging to the most frequent class.
0
Minimal entropy among attributes.
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
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
1.55
Maximum entropy among attributes.
Minimum kurtosis among attributes of the numeric type.
0.2
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.81
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum kurtosis among attributes of the numeric type.
Minimum of means among attributes of the numeric type.
Second quartile (Median) of skewness among attributes of the numeric type.
0.88
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 of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of binary attributes.
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.92
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.
0.49
Maximum mutual information between the nominal attributes and the target attribute.
1
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of instances having missing values.
1.47
Third quartile of entropy among attributes.
0.16
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
18.37
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
10
The maximum number of distinct values among attributes of the nominal type.
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
Third quartile of kurtosis among attributes of the numeric type.
0.1
Average class difference between consecutive instances.
0.82
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Maximum skewness among attributes of the numeric type.
Minimum standard deviation of attributes of the numeric type.
0
Percentage of numeric attributes.
Third quartile of means among attributes of the numeric type.
0.95
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
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.11
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Maximum standard deviation of attributes of the numeric type.
9.86
Percentage of instances belonging to the least frequent class.
100
Percentage of nominal attributes.
0.29
Third quartile of mutual information between the nominal attributes and the target attribute.
0.11
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
0.16
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
0.92
Average entropy of the attributes.
98637
Number of instances belonging to the least frequent class.
0.21
First quartile of entropy among attributes.
Third quartile of skewness among attributes of the numeric type.
0.88
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
0.82
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Mean kurtosis among attributes of the numeric type.
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of kurtosis among attributes of the numeric type.
Third quartile of standard deviation of attributes of the numeric type.
0.95
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
0.92
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.11
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Mean of means among attributes of the numeric type.
0.09
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
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
0.11
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
0.16
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.18
Average mutual information between the nominal attributes and the target attribute.
0.9
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.02
First quartile of mutual information between the nominal attributes and the target attribute.
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.88
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
0.82
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.95
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
4.08
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 skewness among attributes of the numeric type.
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.95
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
0.94
Standard deviation of the number of distinct values among attributes of the nominal type.
0.11
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
3.05
Average number of distinct values among the attributes of the nominal type.
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
0.11
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
0.99
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.88
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
Mean skewness among attributes of the numeric type.

16 tasks

1 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 5 times 2-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 - 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
193 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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