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PieChart1

PieChart1

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Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: pie chart 1

38 features

def (target)nominal2 unique values
0 missing
anumeric52 unique values
0 missing
bnumeric58 unique values
0 missing
cnumeric23 unique values
0 missing
dnumeric24 unique values
0 missing
enumeric53 unique values
0 missing
fnumeric58 unique values
0 missing
gnumeric47 unique values
0 missing
hnumeric69 unique values
0 missing
inumeric38 unique values
0 missing
jnumeric43 unique values
0 missing
knumeric30 unique values
0 missing
lnumeric72 unique values
0 missing
mnumeric106 unique values
0 missing
nnumeric26 unique values
0 missing
onumeric57 unique values
0 missing
pnumeric110 unique values
0 missing
rnumeric7 unique values
0 missing
snumeric654 unique values
0 missing
tnumeric527 unique values
0 missing
unumeric690 unique values
0 missing
vnumeric122 unique values
0 missing
znumeric294 unique values
0 missing
aanumeric28 unique values
0 missing
abnumeric688 unique values
0 missing
acnumeric625 unique values
0 missing
adnumeric71 unique values
0 missing
aenumeric40 unique values
0 missing
afnumeric58 unique values
0 missing
agnumeric88 unique values
0 missing
ahnumeric66 unique values
0 missing
ainumeric194 unique values
0 missing
ajnumeric222 unique values
0 missing
aknumeric101 unique values
0 missing
alnumeric42 unique values
0 missing
amnumeric154 unique values
0 missing
annumeric248 unique values
0 missing
aonumeric109 unique values
0 missing

107 properties

705
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.
264.2
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.
0.08
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.09
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
43415.68
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
5.27
Second quartile (Median) of skewness among attributes of the numeric type.
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
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.
15.25
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.59
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.
2
The maximum number of distinct values among attributes of the nominal type.
-0.06
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.1
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.
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
14.92
Maximum skewness among attributes of the numeric type.
0.06
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
77.22
Third quartile of kurtosis among attributes of the numeric type.
0.84
Average class difference between consecutive instances.
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.09
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
212518.87
Maximum standard deviation of attributes of the numeric type.
8.65
Percentage of instances belonging to the least frequent class.
97.37
Percentage of numeric attributes.
30.72
Third quartile of means among attributes of the numeric type.
0.78
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
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
61
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.
0.09
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
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
56.5
Mean kurtosis among attributes of the numeric type.
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
6.83
Third quartile of skewness among attributes of the numeric type.
0.17
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
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.09
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1283.64
Mean of means among attributes of the numeric type.
0.14
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
15.24
First quartile of kurtosis among attributes of the numeric type.
40.25
Third quartile of standard deviation of attributes of the numeric type.
0.78
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
0.1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.77
First quartile of means among attributes of the numeric type.
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.09
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
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.75
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.
0.08
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.17
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
Standard deviation of the number of distinct values among attributes of the nominal type.
0.09
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.
2.75
First quartile of skewness among attributes of the numeric type.
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.78
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
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
5.35
Mean skewness among attributes of the numeric type.
2.39
First quartile of standard deviation of attributes of the numeric type.
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.09
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
0.11
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
91.35
Percentage of instances belonging to the most frequent class.
6136.71
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.08
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.17
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
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
644
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
42.8
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.42
Entropy of the target attribute values.
Maximum entropy among attributes.
-1.21
Minimum kurtosis among attributes of the numeric type.
11.03
Second quartile (Median) of means among attributes of the numeric type.
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump

6 tasks

102 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
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