Data
BNG(letter,10000,1)

BNG(letter,10000,1)

active ARFF public domain Visibility: public Uploaded 22-02-2015 by Jan van Rijn
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17 features

class (target)nominal26 unique values
0 missing
x-boxnumeric394253 unique values
0 missing
y-boxnumeric828203 unique values
0 missing
widthnumeric387332 unique values
0 missing
highnumeric664853 unique values
0 missing
onpixnumeric539149 unique values
0 missing
x-barnumeric363518 unique values
0 missing
y-barnumeric507928 unique values
0 missing
x2barnumeric629541 unique values
0 missing
y2barnumeric639056 unique values
0 missing
xybarnumeric571628 unique values
0 missing
x2ybrnumeric569743 unique values
0 missing
xy2brnumeric377727 unique values
0 missing
x-egenumeric513913 unique values
0 missing
xegvynumeric326625 unique values
0 missing
y-egenumeric640237 unique values
0 missing
yegvxnumeric325289 unique values
0 missing

107 properties

1000000
Number of instances (rows) of the dataset.
17
Number of attributes (columns) of the dataset.
26
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.
16
Number of numeric attributes.
1
Number of nominal attributes.
1.61
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
0.52
Third quartile of kurtosis among attributes of the numeric type.
0.04
Average class difference between consecutive instances.
0.57
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
1.02
Maximum skewness among attributes of the numeric type.
3.68
Percentage of instances belonging to the least frequent class.
94.12
Percentage of numeric attributes.
7.8
Third quartile of means among attributes of the numeric type.
0.83
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
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.36
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.28
Maximum standard deviation of attributes of the numeric type.
36811
Number of instances belonging to the least frequent class.
5.88
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.36
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
0.42
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
0.88
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.6
Third quartile of skewness among attributes of the numeric type.
0.63
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
0.57
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.15
Mean kurtosis among attributes of the numeric type.
0.57
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.29
First quartile of kurtosis among attributes of the numeric type.
2.48
Third quartile of standard deviation of attributes of the numeric type.
0.83
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
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.36
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
5.94
Mean of means among attributes of the numeric type.
0.41
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
4.17
First quartile of means among attributes of the numeric type.
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.36
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
0.42
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
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.
0.35
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.63
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
0.57
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
26
Average number of distinct values among the attributes of the nominal type.
-0.1
First quartile of skewness among attributes of the numeric type.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.83
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.
0.36
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.28
Mean skewness among attributes of the numeric type.
2
First quartile of standard deviation of attributes of the numeric type.
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.36
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
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.62
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.27
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.35
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.63
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
0.44
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
4.08
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
0.13
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
4.7
Entropy of the target attribute values.
0.54
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
40765
Number of instances belonging to the most frequent class.
-0.54
Minimum kurtosis among attributes of the numeric type.
5.9
Second quartile (Median) of means among attributes of the numeric type.
0.91
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
3.06
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.35
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.93
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
1.01
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.22
Second quartile (Median) of skewness among attributes of the numeric type.
0.64
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.03
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
8.5
Maximum of means among attributes of the numeric type.
26
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
2.25
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.78
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.
-0.3
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.42
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.
26
The maximum number of distinct values among attributes of the nominal type.

11 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - 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
29 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