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KungChi3

KungChi3

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Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: Kung chi

40 features

def (target)nominal2 unique values
0 missing
znumeric122 unique values
0 missing
vnumeric108 unique values
0 missing
aanumeric52 unique values
0 missing
abnumeric95 unique values
0 missing
acnumeric19 unique values
0 missing
adnumeric122 unique values
0 missing
aenumeric121 unique values
0 missing
afnumeric28 unique values
0 missing
agnumeric13 unique values
0 missing
ahnumeric21 unique values
0 missing
ainumeric51 unique values
0 missing
ajnumeric29 unique values
0 missing
aknumeric70 unique values
0 missing
alnumeric83 unique values
0 missing
amnumeric48 unique values
0 missing
annumeric20 unique values
0 missing
aonumeric56 unique values
0 missing
apnumeric41 unique values
0 missing
arnumeric51 unique values
0 missing
knumeric16 unique values
0 missing
bnumeric23 unique values
0 missing
cnumeric27 unique values
0 missing
dnumeric3 unique values
0 missing
enumeric12 unique values
0 missing
fnumeric21 unique values
0 missing
gnumeric15 unique values
0 missing
hnumeric27 unique values
0 missing
inumeric13 unique values
0 missing
jnumeric12 unique values
0 missing
anumeric20 unique values
0 missing
lnumeric18 unique values
0 missing
mnumeric56 unique values
0 missing
nnumeric9 unique values
0 missing
onumeric16 unique values
0 missing
pnumeric49 unique values
0 missing
rnumeric4 unique values
0 missing
snumeric16 unique values
0 missing
tnumeric19 unique values
0 missing
unumeric122 unique values
0 missing
Show all 40 features

107 properties

NumberOfInstances
123
Number of instances (rows) of the dataset.
NumberOfFeatures
40
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
39
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.81
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.7
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
0.12
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
0.24
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
0.77
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
0.15
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
0.34
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
0.16
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
0.28
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
0.56
Entropy of the target attribute values.
DecisionStumpAUC
0.7
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
0.24
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.33
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
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.29
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
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.29
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
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.29
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
86.99
Percentage of instances belonging to the most frequent class.
MajorityClassSize
107
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
15.63
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
20366.84
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
3.73
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
38139.59
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
6.13
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
589.03
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
2.06
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
1072.55
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.75
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
-1.57
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.04
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
13.01
Percentage of instances belonging to the least frequent class.
MinorityClassSize
16
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.68
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.18
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
2.5
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
97.5
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
2.5
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
2.33
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.9
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
1.61
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.34
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
6.19
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
5.53
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
2.32
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
5.66
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
8.82
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
27.59
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
2.69
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
25.02
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
0.13
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
0.13
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
0.13
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
0.13
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
0.56
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
-0.07
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.44
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
-0.07
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
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.11
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.4
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

12 tasks

Supervised Classification on KungChi3
1 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: matthews_correlation_coefficient - target_feature: def
Clustering on KungChi3
0 runs
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KungChi3
0 runs - estimation_procedure: 50 times Clustering
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