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KnuggetChase3

KnuggetChase3

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Author: Hans Bauer Jesus","Deter Bergman Source: Unknown - Date unknown Please cite: knugget chase 3

40 features

def (target)nominal2 unique values
0 missing
znumeric189 unique values
0 missing
vnumeric168 unique values
0 missing
aanumeric74 unique values
0 missing
abnumeric139 unique values
0 missing
acnumeric19 unique values
0 missing
adnumeric189 unique values
0 missing
aenumeric186 unique values
0 missing
afnumeric37 unique values
0 missing
agnumeric17 unique values
0 missing
ahnumeric28 unique values
0 missing
ainumeric73 unique values
0 missing
ajnumeric32 unique values
0 missing
aknumeric104 unique values
0 missing
alnumeric124 unique values
0 missing
amnumeric65 unique values
0 missing
annumeric24 unique values
0 missing
aonumeric82 unique values
0 missing
apnumeric76 unique values
0 missing
arnumeric71 unique values
0 missing
knumeric21 unique values
0 missing
bnumeric33 unique values
0 missing
cnumeric33 unique values
0 missing
dnumeric6 unique values
0 missing
enumeric20 unique values
0 missing
fnumeric28 unique values
0 missing
gnumeric23 unique values
0 missing
hnumeric30 unique values
0 missing
inumeric15 unique values
0 missing
jnumeric21 unique values
0 missing
anumeric25 unique values
0 missing
lnumeric27 unique values
0 missing
mnumeric82 unique values
0 missing
nnumeric13 unique values
0 missing
onumeric26 unique values
0 missing
pnumeric69 unique values
0 missing
rnumeric4 unique values
0 missing
snumeric21 unique values
0 missing
tnumeric29 unique values
0 missing
unumeric188 unique values
0 missing
Show all 40 features

107 properties

NumberOfInstances
194
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
0.72
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.66
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
0.16
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
0.39
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
0.67
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
CfsSubsetEval_NaiveBayesErrRate
0.19
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
0.17
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
0.18
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
0.18
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
0.69
Entropy of the target attribute values.
DecisionStumpAUC
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.18
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.21
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
0.19
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
0.19
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
0.19
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
81.44
Percentage of instances belonging to the most frequent class.
MajorityClassSize
158
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
62.03
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
30965.46
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
6.87
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
64279.04
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
9.24
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
886.33
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
2.27
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
1796.88
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-0.57
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.07
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
-1.3
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.04
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
18.56
Percentage of instances belonging to the least frequent class.
MinorityClassSize
36
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
0.22
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.28
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
2.9
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
0.95
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
1.53
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
0.85
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
6.23
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
6.63
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
2.23
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
6.58
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
10.9
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
33.69
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
2.76
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
34.19
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
0.19
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
0.19
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
0.19
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
0.66
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
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.64
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
0.21
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
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.27
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

12 tasks

Supervised Classification on KnuggetChase3
0 runs - estimation_procedure: 33% Holdout set - target_feature: def
Clustering on KnuggetChase3
0 runs
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
Clustering on KnuggetChase3
0 runs - estimation_procedure: 50 times Clustering
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