Data
PizzaCutter3

PizzaCutter3

active ARFF Publicly available Visibility: public Uploaded 19-05-2015 by Hans Bauer
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Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: Pizza cutter 3

38 features

def (target)nominal2 unique values
0 missing
anumeric52 unique values
0 missing
bnumeric66 unique values
0 missing
cnumeric19 unique values
0 missing
dnumeric25 unique values
0 missing
enumeric57 unique values
0 missing
fnumeric66 unique values
0 missing
gnumeric50 unique values
0 missing
hnumeric76 unique values
0 missing
inumeric42 unique values
0 missing
jnumeric47 unique values
0 missing
knumeric31 unique values
0 missing
lnumeric75 unique values
0 missing
mnumeric116 unique values
0 missing
nnumeric25 unique values
0 missing
onumeric59 unique values
0 missing
pnumeric115 unique values
0 missing
rnumeric8 unique values
0 missing
snumeric929 unique values
0 missing
tnumeric700 unique values
0 missing
unumeric1017 unique values
0 missing
vnumeric129 unique values
0 missing
znumeric326 unique values
0 missing
aanumeric29 unique values
0 missing
abnumeric1014 unique values
0 missing
acnumeric877 unique values
0 missing
adnumeric80 unique values
0 missing
aenumeric48 unique values
0 missing
afnumeric65 unique values
0 missing
agnumeric95 unique values
0 missing
ahnumeric67 unique values
0 missing
ainumeric214 unique values
0 missing
ajnumeric242 unique values
0 missing
aknumeric113 unique values
0 missing
alnumeric38 unique values
0 missing
amnumeric160 unique values
0 missing
annumeric334 unique values
0 missing
aonumeric117 unique values
0 missing

107 properties

1043
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.
871.24
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.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.12
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
41989.19
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
9.03
Second quartile (Median) of skewness among attributes of the numeric type.
0.11
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.
14.38
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.63
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.
2
The maximum number of distinct values among attributes of the nominal type.
0.04
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.17
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.
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
28.54
Maximum skewness among attributes of the numeric type.
0.06
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
317.9
Third quartile of kurtosis among attributes of the numeric type.
0.78
Average class difference between consecutive instances.
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
412208.56
Maximum standard deviation of attributes of the numeric type.
12.18
Percentage of instances belonging to the least frequent class.
97.37
Percentage of numeric attributes.
28.46
Third quartile of means among attributes of the numeric type.
0.6
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
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
127
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.
0.13
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
0.17
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
189.28
Mean kurtosis among attributes of the numeric type.
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
14.98
Third quartile of skewness among attributes of the numeric type.
0.07
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
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1243.54
Mean of means among attributes of the numeric type.
0.51
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
8.81
First quartile of kurtosis among attributes of the numeric type.
50.64
Third quartile of standard deviation of attributes of the numeric type.
0.6
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
0.17
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.94
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
0.13
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
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.67
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.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.07
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.
0.14
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.
2.35
First quartile of skewness among attributes of the numeric type.
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.6
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
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
9.46
Mean skewness among attributes of the numeric type.
2.14
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
0.13
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
0.16
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
87.82
Percentage of instances belonging to the most frequent class.
11897.95
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.07
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
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
916
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
115.66
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.53
Entropy of the target attribute values.
Maximum entropy among attributes.
-1.15
Minimum kurtosis among attributes of the numeric type.
10.61
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
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump

7 tasks

97 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: matthews_correlation_coefficient - target_feature: def
91 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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