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PieChart2

PieChart2

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Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: pie chart 2

37 features

def (target)nominal2 unique values
0 missing
anumeric36 unique values
0 missing
bnumeric28 unique values
0 missing
cnumeric72 unique values
0 missing
dnumeric55 unique values
0 missing
enumeric35 unique values
0 missing
fnumeric26 unique values
0 missing
gnumeric59 unique values
0 missing
hnumeric22 unique values
0 missing
inumeric28 unique values
0 missing
jnumeric21 unique values
0 missing
knumeric40 unique values
0 missing
lnumeric75 unique values
0 missing
mnumeric19 unique values
0 missing
nnumeric2 unique values
0 missing
onumeric17 unique values
0 missing
pnumeric11 unique values
0 missing
rnumeric614 unique values
0 missing
snumeric399 unique values
0 missing
tnumeric691 unique values
0 missing
unumeric75 unique values
0 missing
vnumeric195 unique values
0 missing
znumeric32 unique values
0 missing
aanumeric680 unique values
0 missing
abnumeric500 unique values
0 missing
acnumeric40 unique values
0 missing
adnumeric24 unique values
0 missing
aenumeric35 unique values
0 missing
afnumeric66 unique values
0 missing
agnumeric54 unique values
0 missing
ahnumeric119 unique values
0 missing
ainumeric146 unique values
0 missing
ajnumeric56 unique values
0 missing
aknumeric31 unique values
0 missing
alnumeric102 unique values
0 missing
amnumeric147 unique values
0 missing
annumeric76 unique values
0 missing

107 properties

745
Number of instances (rows) of the dataset.
37
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.
36
Number of numeric attributes.
1
Number of nominal attributes.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.04
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
0.49
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
8.35
Mean skewness among attributes of the numeric type.
2.5
First quartile of standard deviation of attributes of the numeric type.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
-0.02
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
97.85
Percentage of instances belonging to the most frequent class.
1538.11
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.15
Entropy of the target attribute values.
-0.02
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
729
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
108.79
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.04
Minimum kurtosis among attributes of the numeric type.
6.79
Second quartile (Median) of means among attributes of the numeric type.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.02
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
419.56
Maximum kurtosis among attributes of the numeric type.
0.11
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
12641.47
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
8.85
Second quartile (Median) of skewness among attributes of the numeric type.
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.05
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.
2.7
Percentage of binary attributes.
12.59
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.02
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.
-2.67
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
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
18.37
Maximum skewness among attributes of the numeric type.
0.08
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
225.25
Third quartile of kurtosis among attributes of the numeric type.
0.96
Average class difference between consecutive instances.
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
50872.76
Maximum standard deviation of attributes of the numeric type.
2.15
Percentage of instances belonging to the least frequent class.
97.3
Percentage of numeric attributes.
21.66
Third quartile of means among attributes of the numeric type.
0.71
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
0.02
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.
16
Number of instances belonging to the least frequent class.
2.7
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.02
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
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
133.86
Mean kurtosis among attributes of the numeric type.
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
12.82
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
0.65
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
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
394.72
Mean of means among attributes of the numeric type.
0.2
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
20.99
First quartile of kurtosis among attributes of the numeric type.
33.07
Third quartile of standard deviation of attributes of the numeric type.
0.05
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
0.02
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.
0
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.16
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
-0.02
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
0.5
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.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.64
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.
0.02
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.
3.76
First quartile of skewness among attributes of the numeric type.

11 tasks

101 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: def
0 runs - estimation_procedure: 33% Holdout set - 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
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