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PieChart2

PieChart2

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Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: pie chart 2

37 features

def (target)nominal2 unique values
0 missing
unumeric75 unique values
0 missing
tnumeric691 unique values
0 missing
vnumeric195 unique values
0 missing
znumeric32 unique values
0 missing
aanumeric680 unique values
0 missing
abnumeric500 unique values
0 missing
acnumeric40 unique values
0 missing
adnumeric24 unique values
0 missing
aenumeric35 unique values
0 missing
afnumeric66 unique values
0 missing
agnumeric54 unique values
0 missing
ahnumeric119 unique values
0 missing
ainumeric146 unique values
0 missing
ajnumeric56 unique values
0 missing
aknumeric31 unique values
0 missing
alnumeric102 unique values
0 missing
amnumeric147 unique values
0 missing
annumeric76 unique values
0 missing
jnumeric21 unique values
0 missing
bnumeric28 unique values
0 missing
cnumeric72 unique values
0 missing
dnumeric55 unique values
0 missing
enumeric35 unique values
0 missing
fnumeric26 unique values
0 missing
gnumeric59 unique values
0 missing
hnumeric22 unique values
0 missing
inumeric28 unique values
0 missing
anumeric36 unique values
0 missing
knumeric40 unique values
0 missing
lnumeric75 unique values
0 missing
mnumeric19 unique values
0 missing
nnumeric2 unique values
0 missing
onumeric17 unique values
0 missing
pnumeric11 unique values
0 missing
rnumeric614 unique values
0 missing
snumeric399 unique values
0 missing
Show all 37 features

107 properties

NumberOfInstances
745
Number of instances (rows) of the dataset.
NumberOfFeatures
37
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
36
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.96
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.71
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
0.02
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
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
0.65
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
0.05
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
-0.02
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
0.64
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
0.04
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
-0.02
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
0.15
Entropy of the target attribute values.
DecisionStumpAUC
0.78
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.05
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
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
97.85
Percentage of instances belonging to the most frequent class.
MajorityClassSize
729
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
419.56
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
12641.47
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
18.37
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
50872.76
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
133.86
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
394.72
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
8.35
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
1538.11
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.04
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.11
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
-2.67
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.08
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
2.15
Percentage of instances belonging to the least frequent class.
MinorityClassSize
16
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.55
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.2
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
2.7
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
97.3
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
2.7
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
20.99
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
2.16
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
3.76
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
2.5
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
108.79
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
6.79
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
8.85
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
12.59
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
225.25
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
21.66
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
12.82
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
33.07
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0
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
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.57
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.62
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.02
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0
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
0.49
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.05
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
-0.02
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

13 tasks

Supervised Classification on PieChart2
101 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: def
Supervised Classification on PieChart2
0 runs - estimation_procedure: 33% Holdout set - target_feature: def
Clustering on PieChart2
0 runs
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
Clustering on PieChart2
0 runs - estimation_procedure: 50 times Clustering
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