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CastMetal1

CastMetal1

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: cast metal 1

38 features

def (target)nominal2 unique values
0 missing
anumeric59 unique values
0 missing
bnumeric40 unique values
0 missing
cnumeric20 unique values
0 missing
dnumeric35 unique values
0 missing
enumeric67 unique values
0 missing
fnumeric45 unique values
0 missing
gnumeric31 unique values
0 missing
hnumeric31 unique values
0 missing
inumeric27 unique values
0 missing
jnumeric36 unique values
0 missing
knumeric28 unique values
0 missing
lnumeric54 unique values
0 missing
mnumeric83 unique values
0 missing
nnumeric17 unique values
0 missing
onumeric36 unique values
0 missing
pnumeric98 unique values
0 missing
rnumeric11 unique values
0 missing
snumeric313 unique values
0 missing
tnumeric284 unique values
0 missing
unumeric325 unique values
0 missing
vnumeric104 unique values
0 missing
znumeric210 unique values
0 missing
aanumeric25 unique values
0 missing
abnumeric325 unique values
0 missing
acnumeric312 unique values
0 missing
adnumeric52 unique values
0 missing
aenumeric27 unique values
0 missing
afnumeric45 unique values
0 missing
agnumeric73 unique values
0 missing
ahnumeric29 unique values
0 missing
ainumeric148 unique values
0 missing
ajnumeric173 unique values
0 missing
aknumeric92 unique values
0 missing
alnumeric42 unique values
0 missing
amnumeric144 unique values
0 missing
annumeric227 unique values
0 missing
aonumeric103 unique values
0 missing

107 properties

327
Number of instances (rows) of the dataset.
38
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.
37
Number of numeric attributes.
1
Number of nominal attributes.
3.53
Second quartile (Median) of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
49208.27
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
15.1
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.12
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.
2.63
Percentage of binary attributes.
Third quartile of entropy among attributes.
0.22
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.
-0.45
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
27.7
Third quartile of kurtosis among attributes of the numeric type.
0.77
Average class difference between consecutive instances.
0.06
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
9.25
Maximum skewness among attributes of the numeric type.
0.06
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
44.02
Third quartile of means among attributes of the numeric type.
0.53
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
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.17
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
160345.25
Maximum standard deviation of attributes of the numeric type.
12.84
Percentage of instances belonging to the least frequent class.
97.37
Percentage of numeric attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
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
0.22
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
42
Number of instances belonging to the least frequent class.
2.63
Percentage of nominal attributes.
4.35
Third quartile of skewness among attributes of the numeric type.
0.02
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
0.06
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.67
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
22.63
Mean kurtosis among attributes of the numeric type.
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
9.44
First quartile of kurtosis among attributes of the numeric type.
45.31
Third quartile of standard deviation of attributes of the numeric type.
0.53
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
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.17
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1462.39
Mean of means among attributes of the numeric type.
0.22
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
2.6
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
0.13
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
0.22
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.16
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of mutual information between the nominal attributes and the target attribute.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.06
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.67
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.
2.44
First quartile of skewness among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.53
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.
0.17
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.
2.93
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
0.13
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
0.51
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
3.57
Mean skewness among attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
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
0.23
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
87.16
Percentage of instances belonging to the most frequent class.
4655.67
Mean standard deviation of attributes of the numeric type.
17.62
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.55
Entropy of the target attribute values.
0
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
285
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
16.77
Second quartile (Median) of means among attributes of the numeric type.
0.5
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.65
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-1.08
Minimum kurtosis among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.13
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.13
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
104.33
Maximum kurtosis among attributes of the numeric type.
0.08
Minimum of means among attributes of the numeric type.

13 tasks

111 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: def
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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