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PieChart3

PieChart3

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Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: pie chart 3

38 features

def (target)nominal2 unique values
0 missing
anumeric54 unique values
0 missing
bnumeric70 unique values
0 missing
cnumeric19 unique values
0 missing
dnumeric25 unique values
0 missing
enumeric57 unique values
0 missing
fnumeric68 unique values
0 missing
gnumeric52 unique values
0 missing
hnumeric76 unique values
0 missing
inumeric44 unique values
0 missing
jnumeric51 unique values
0 missing
knumeric33 unique values
0 missing
lnumeric77 unique values
0 missing
mnumeric123 unique values
0 missing
nnumeric25 unique values
0 missing
onumeric61 unique values
0 missing
pnumeric118 unique values
0 missing
rnumeric8 unique values
0 missing
snumeric959 unique values
0 missing
tnumeric723 unique values
0 missing
unumeric1051 unique values
0 missing
vnumeric137 unique values
0 missing
znumeric339 unique values
0 missing
aanumeric30 unique values
0 missing
abnumeric1048 unique values
0 missing
acnumeric907 unique values
0 missing
adnumeric81 unique values
0 missing
aenumeric49 unique values
0 missing
afnumeric67 unique values
0 missing
agnumeric101 unique values
0 missing
ahnumeric67 unique values
0 missing
ainumeric222 unique values
0 missing
ajnumeric250 unique values
0 missing
aknumeric115 unique values
0 missing
alnumeric39 unique values
0 missing
amnumeric169 unique values
0 missing
annumeric350 unique values
0 missing
aonumeric122 unique values
0 missing

107 properties

1077
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.
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
0.18
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
134
Number of instances belonging to the least frequent class.
2.63
Percentage of nominal attributes.
14.53
Third quartile of skewness among attributes of the numeric type.
0.05
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
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
176.74
Mean kurtosis among attributes of the numeric type.
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
50.92
Third quartile of standard deviation of attributes of the numeric type.
0.63
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
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.15
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1405.31
Mean of means among attributes of the numeric type.
0.51
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
8.26
First quartile of kurtosis among attributes of the numeric type.
0.76
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
0.18
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.1
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.99
First quartile of means among attributes of the numeric type.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.05
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
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.55
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.
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.63
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.
0.15
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.
2.32
First quartile of skewness among attributes of the numeric type.
0.76
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
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
9.14
Mean skewness among attributes of the numeric type.
2.19
First quartile of standard deviation of attributes of the numeric type.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.05
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
0.18
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
87.56
Percentage of instances belonging to the most frequent class.
12424.52
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.54
Entropy of the target attribute values.
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
943
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
111.29
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.13
Minimum kurtosis among attributes of the numeric type.
10.9
Second quartile (Median) of means among attributes of the numeric type.
0.14
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.12
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
718.88
Maximum kurtosis among attributes of the numeric type.
0.08
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
47604.2
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
8.75
Second quartile (Median) of skewness among attributes of the numeric type.
16.81
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.04
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.
2.63
Percentage of binary attributes.
Third quartile of entropy among attributes.
0.18
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.
0.02
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
304.56
Third quartile of kurtosis among attributes of the numeric type.
0.77
Average class difference between consecutive instances.
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
25.38
Maximum skewness among attributes of the numeric type.
0.06
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
29.39
Third quartile of means among attributes of the numeric type.
0.63
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
0.56
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.15
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
430669.62
Maximum standard deviation of attributes of the numeric type.
12.44
Percentage of instances belonging to the least frequent class.
97.37
Percentage of numeric attributes.

5 tasks

103 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
Define a new task