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KnuggetChase3

KnuggetChase3

active ARFF Publicly available Visibility: public Uploaded 20-05-2015 by Hans Bauer
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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
anumeric25 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
knumeric21 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
vnumeric168 unique values
0 missing
znumeric189 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

107 properties

194
Number of instances (rows) of the dataset.
40
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.
39
Number of numeric attributes.
1
Number of nominal attributes.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
30965.46
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
2.23
Second quartile (Median) of skewness among attributes of the numeric type.
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.21
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.
2.5
Percentage of binary attributes.
6.58
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.17
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.
-1.3
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.25
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
6.87
Maximum skewness among attributes of the numeric type.
0.04
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
10.9
Third quartile of kurtosis among attributes of the numeric type.
0.72
Average class difference between consecutive instances.
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.19
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
64279.04
Maximum standard deviation of attributes of the numeric type.
18.56
Percentage of instances belonging to the least frequent class.
97.5
Percentage of numeric attributes.
33.69
Third quartile of means among attributes of the numeric type.
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
0.19
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
36
Number of instances belonging to the least frequent class.
2.5
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
0.23
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
9.24
Mean kurtosis among attributes of the numeric type.
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
2.76
Third quartile of skewness among attributes of the numeric type.
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
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.19
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
886.33
Mean of means among attributes of the numeric type.
0.22
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.9
First quartile of kurtosis among attributes of the numeric type.
34.19
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
0.17
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.28
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0.95
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
0.19
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
0.21
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.5
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.
First quartile of mutual information between the nominal attributes and the target attribute.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
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
0
Standard deviation of the number of distinct values among attributes of the nominal type.
0.19
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.
1.53
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.27
Mean skewness among attributes of the numeric type.
0.85
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
0.18
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
0.27
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
81.44
Percentage of instances belonging to the most frequent class.
1796.88
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.69
Entropy of the target attribute values.
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
158
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
6.23
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.57
Minimum kurtosis among attributes of the numeric type.
6.63
Second quartile (Median) of means among attributes of the numeric type.
0.19
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.18
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
62.03
Maximum kurtosis among attributes of the numeric type.
0.07
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

12 tasks

0 runs - estimation_procedure: 33% Holdout set - target_feature: def
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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