Data
PizzaCutter1

PizzaCutter1

active ARFF Publicly available Visibility: public Uploaded 19-05-2015 by Hans Bauer
0 likes downloaded by 8 people , 8 total downloads 0 issues 0 downvotes
  • origin_unknown study_52 study_7
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: Pizza cutter

38 features

def (target)nominal2 unique values
0 missing
anumeric47 unique values
0 missing
bnumeric55 unique values
0 missing
cnumeric23 unique values
0 missing
dnumeric22 unique values
0 missing
enumeric45 unique values
0 missing
fnumeric56 unique values
0 missing
gnumeric41 unique values
0 missing
hnumeric68 unique values
0 missing
inumeric34 unique values
0 missing
jnumeric40 unique values
0 missing
knumeric29 unique values
0 missing
lnumeric67 unique values
0 missing
mnumeric96 unique values
0 missing
nnumeric26 unique values
0 missing
onumeric51 unique values
0 missing
pnumeric102 unique values
0 missing
rnumeric7 unique values
0 missing
snumeric613 unique values
0 missing
tnumeric490 unique values
0 missing
unumeric648 unique values
0 missing
vnumeric110 unique values
0 missing
znumeric273 unique values
0 missing
aanumeric27 unique values
0 missing
abnumeric646 unique values
0 missing
acnumeric586 unique values
0 missing
adnumeric67 unique values
0 missing
aenumeric38 unique values
0 missing
afnumeric57 unique values
0 missing
agnumeric80 unique values
0 missing
ahnumeric65 unique values
0 missing
ainumeric180 unique values
0 missing
ajnumeric204 unique values
0 missing
aknumeric88 unique values
0 missing
alnumeric40 unique values
0 missing
amnumeric137 unique values
0 missing
annumeric226 unique values
0 missing
aonumeric101 unique values
0 missing

107 properties

661
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.
2.63
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.08
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
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
52
Number of instances belonging to the least frequent class.
First quartile of entropy among attributes.
7.82
Third quartile of skewness among attributes of the numeric type.
0.19
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
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
62.67
Mean kurtosis among attributes of the numeric type.
0.76
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
11.84
First quartile of kurtosis among attributes of the numeric type.
38.41
Third quartile of standard deviation of attributes of the numeric type.
0.67
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
0.55
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
962.84
Mean of means among attributes of the numeric type.
0.11
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.69
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
0.08
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
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
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
0.19
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
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.74
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.
2.78
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.67
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.
0.09
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.
2.25
First quartile of standard deviation of attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.08
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
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
5.66
Mean skewness among 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
0.19
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
0.11
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
92.13
Percentage of instances belonging to the most frequent class.
3961.85
Mean standard deviation of attributes of the numeric type.
47.76
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.4
Entropy of the target attribute values.
0.22
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
609
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
10.38
Second quartile (Median) of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.24
Minimum kurtosis 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
0.08
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
257.3
Maximum kurtosis among attributes of the numeric type.
0.08
Minimum of means among attributes of the numeric type.
5.82
Second quartile (Median) of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
32323.67
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
14.45
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.06
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.
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.
-0.06
Minimum skewness among attributes of the numeric type.
0
Percentage of missing values.
97.82
Third quartile of kurtosis among attributes of the numeric type.
0.85
Average class difference between consecutive instances.
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.74
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
14.49
Maximum skewness among attributes of the numeric type.
0.06
Minimum standard deviation of attributes of the numeric type.
97.37
Percentage of numeric attributes.
28.56
Third quartile of means among attributes of the numeric type.
0.67
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
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.09
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
136511.38
Maximum standard deviation of attributes of the numeric type.
7.87
Percentage of instances belonging to the least frequent class.

6 tasks

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