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PieChart4

PieChart4

deactivated ARFF Publicly available Visibility: public Uploaded 20-05-2015 by Hans Bauer
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Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: pie chart 4 Deactivated: this is a duplicate of https://www.openml.org/d/1049

38 features

def (target)nominal2 unique values
0 missing
anumeric54 unique values
0 missing
bnumeric61 unique values
0 missing
cnumeric22 unique values
0 missing
dnumeric36 unique values
0 missing
enumeric57 unique values
0 missing
fnumeric41 unique values
0 missing
gnumeric43 unique values
0 missing
hnumeric70 unique values
0 missing
inumeric23 unique values
0 missing
jnumeric5 unique values
0 missing
knumeric31 unique values
0 missing
lnumeric76 unique values
0 missing
mnumeric105 unique values
0 missing
nnumeric25 unique values
0 missing
onumeric2 unique values
0 missing
pnumeric107 unique values
0 missing
rnumeric8 unique values
0 missing
snumeric1021 unique values
0 missing
tnumeric708 unique values
0 missing
unumeric1165 unique values
0 missing
vnumeric120 unique values
0 missing
znumeric336 unique values
0 missing
aanumeric40 unique values
0 missing
abnumeric1159 unique values
0 missing
acnumeric941 unique values
0 missing
adnumeric74 unique values
0 missing
aenumeric28 unique values
0 missing
afnumeric40 unique values
0 missing
agnumeric89 unique values
0 missing
ahnumeric67 unique values
0 missing
ainumeric184 unique values
0 missing
ajnumeric245 unique values
0 missing
aknumeric71 unique values
0 missing
alnumeric38 unique values
0 missing
amnumeric171 unique values
0 missing
annumeric394 unique values
0 missing
aonumeric116 unique values
0 missing

107 properties

1458
Number of instances (rows) of the dataset.
38
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.
37
Number of numeric attributes.
1
Number of nominal attributes.
2.02
First quartile of standard deviation of attributes of the numeric type.
0.87
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
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
6.45
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.34
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
0.15
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
87.79
Percentage of instances belonging to the most frequent class.
1837.83
Mean standard deviation of attributes of the numeric type.
48.05
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.33
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.54
Entropy of the target attribute values.
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
1280
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
7
Second quartile (Median) of means among attributes of the numeric type.
0.86
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.51
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.1
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.12
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
771.63
Maximum kurtosis among attributes of the numeric type.
0.07
Minimum of means among attributes of the numeric type.
5.71
Second quartile (Median) of skewness among attributes of the numeric type.
0.31
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
19505.52
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
2.63
Percentage of binary attributes.
9.49
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.03
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
-0.46
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.12
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.
0.12
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
173.88
Third quartile of kurtosis among attributes of the numeric type.
0.78
Average class difference between consecutive instances.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
25.48
Maximum skewness among attributes of the numeric type.
12.21
Percentage of instances belonging to the least frequent class.
97.37
Percentage of numeric attributes.
19.71
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
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
62600.26
Maximum standard deviation of attributes of the numeric type.
178
Number of instances belonging to the least frequent class.
2.63
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.12
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
0.12
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
0.82
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
9.49
Third quartile of skewness among attributes of the numeric type.
0
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
105.09
Mean kurtosis among attributes of the numeric type.
0.17
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
9.74
First quartile of kurtosis among attributes of the numeric type.
26.37
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
0.85
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
583.46
Mean of means among attributes of the numeric type.
0.3
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.47
First quartile of means among attributes of the numeric type.
0.5
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
0.12
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.12
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.34
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
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.86
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.
2.82
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.81
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.
0.1
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
2
Average number of distinct values among the attributes of the nominal type.

12 tasks

112 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: def
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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