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PizzaCutter3

PizzaCutter3

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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
vnumeric129 unique values
0 missing
unumeric1017 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
knumeric31 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
anumeric52 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
Show all 38 features

107 properties

NumberOfInstances
1043
Number of instances (rows) of the dataset.
NumberOfFeatures
38
Number of attributes (columns) of the dataset.
NumberOfClasses
2
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
37
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.78
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
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
CfsSubsetEval_DecisionStumpErrRate
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
CfsSubsetEval_DecisionStumpKappa
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
CfsSubsetEval_NaiveBayesAUC
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
CfsSubsetEval_NaiveBayesErrRate
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
CfsSubsetEval_NaiveBayesKappa
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
CfsSubsetEval_kNN1NAUC
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
CfsSubsetEval_kNN1NErrRate
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
CfsSubsetEval_kNN1NKappa
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
ClassEntropy
0.53
Entropy of the target attribute values.
DecisionStumpAUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.04
Number of attributes divided by the number of instances.
EquivalentNumberOfAtts
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
J48.00001.AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.14
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
87.82
Percentage of instances belonging to the most frequent class.
MajorityClassSize
916
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
871.24
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
41989.19
Maximum of means among attributes of the numeric type.
MaxMutualInformation
Maximum mutual information between the nominal attributes and the target attribute.
MaxNominalAttDistinctValues
2
The maximum number of distinct values among attributes of the nominal type.
MaxSkewnessOfNumericAtts
28.54
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
412208.56
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
189.28
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
1243.54
Mean of means among attributes of the numeric type.
MeanMutualInformation
Average mutual information between the nominal attributes and the target attribute.
MeanNoiseToSignalRatio
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
MeanNominalAttDistinctValues
2
Average number of distinct values among the attributes of the nominal type.
MeanSkewnessOfNumericAtts
9.46
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
11897.95
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.15
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.08
Minimum of means among attributes of the numeric type.
MinMutualInformation
Minimal mutual information between the nominal attributes and the target attribute.
MinNominalAttDistinctValues
2
The minimal number of distinct values among attributes of the nominal type.
MinSkewnessOfNumericAtts
0.04
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.06
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
12.18
Percentage of instances belonging to the least frequent class.
MinorityClassSize
127
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.51
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
2.63
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
97.37
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
2.63
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
8.81
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
1.94
First quartile of means among attributes of the numeric type.
Quartile1MutualInformation
First quartile of mutual information between the nominal attributes and the target attribute.
Quartile1SkewnessOfNumericAtts
2.35
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
2.14
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
115.66
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
10.61
Second quartile (Median) of means among attributes of the numeric type.
Quartile2MutualInformation
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Quartile2SkewnessOfNumericAtts
9.03
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
14.38
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
317.9
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
28.46
Third quartile of means among attributes of the numeric type.
Quartile3MutualInformation
Third quartile of mutual information between the nominal attributes and the target attribute.
Quartile3SkewnessOfNumericAtts
14.98
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
50.64
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.73
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.17
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.17
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.63
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.17
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
StdvNominalAttDistinctValues
0
Standard deviation of the number of distinct values among attributes of the nominal type.
kNN1NAUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

14 tasks

Supervised Classification on PizzaCutter3
97 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: matthews_correlation_coefficient - target_feature: def
Supervised Classification on PizzaCutter3
91 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: def
Supervised Classification on PizzaCutter3
0 runs - estimation_procedure: 33% Holdout set - target_feature: def
Clustering on PizzaCutter3
0 runs
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
Clustering on PizzaCutter3
0 runs - estimation_procedure: 50 times Clustering
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