Data
ar5

ar5

active ARFF Publicly available Visibility: public Uploaded 06-10-2014 by Joaquin Vanschoren
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  • Chemistry Life Science mythbusting_1 PROMISE study_1 study_123 study_15 study_20 study_41
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30 features

defects (target)nominal2 unique values
0 missing
total_locnumeric32 unique values
0 missing
blank_locnumeric24 unique values
0 missing
comment_locnumeric18 unique values
0 missing
code_and_comment_locnumeric6 unique values
0 missing
executable_locnumeric30 unique values
0 missing
unique_operandsnumeric29 unique values
0 missing
unique_operatorsnumeric17 unique values
0 missing
total_operandsnumeric35 unique values
0 missing
total_operatorsnumeric35 unique values
0 missing
halstead_vocabularynumeric31 unique values
0 missing
halstead_lengthnumeric34 unique values
0 missing
halstead_volumenumeric36 unique values
0 missing
halstead_levelnumeric35 unique values
0 missing
halstead_difficultynumeric35 unique values
0 missing
halstead_effortnumeric36 unique values
0 missing
halstead_errornumeric36 unique values
0 missing
halstead_timenumeric36 unique values
0 missing
branch_countnumeric22 unique values
0 missing
decision_countnumeric22 unique values
0 missing
call_pairsnumeric13 unique values
0 missing
condition_countnumeric21 unique values
0 missing
multiple_condition_countnumeric14 unique values
0 missing
cyclomatic_complexitynumeric20 unique values
0 missing
cyclomatic_densitynumeric34 unique values
0 missing
decision_densitynumeric14 unique values
0 missing
design_complexitynumeric13 unique values
0 missing
design_densitynumeric24 unique values
0 missing
normalized_cyclomatic_complexitynumeric35 unique values
0 missing
formal_parametersnumeric3 unique values
0 missing

107 properties

36
Number of instances (rows) of the dataset.
30
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.
29
Number of numeric attributes.
1
Number of nominal attributes.
0.16
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.41
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
30280.89
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
2.17
Second quartile (Median) of skewness among attributes of the numeric type.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.83
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.
3.33
Percentage of binary attributes.
18.21
Second quartile (Median) of standard deviation of attributes of the numeric type.
0.28
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.
0.22
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
3.81
Maximum skewness among attributes of the numeric type.
0.1
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
9.04
Third quartile of kurtosis among attributes of the numeric type.
0.69
Average class difference between consecutive instances.
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.22
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
56745.79
Maximum standard deviation of attributes of the numeric type.
22.22
Percentage of instances belonging to the least frequent class.
96.67
Percentage of numeric attributes.
62.38
Third quartile of means among attributes of the numeric type.
0.77
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
0.28
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.41
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
8
Number of instances belonging to the least frequent class.
3.33
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
0.22
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
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
0.77
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
6.69
Mean kurtosis among attributes of the numeric type.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
2.59
Third quartile of skewness among attributes of the numeric type.
0.45
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
0.69
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.22
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
1162.29
Mean of means among attributes of the numeric type.
0.17
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
3.89
First quartile of kurtosis among attributes of the numeric type.
72.95
Third quartile of standard deviation of attributes of the numeric type.
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
0.28
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.41
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Average mutual information between the nominal attributes and the target attribute.
0.56
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
1.23
First quartile of means among attributes of the numeric type.
0.61
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.22
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
0.32
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
0.77
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.
0.25
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.45
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
0.77
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.
0.22
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.
1.77
First quartile of skewness among attributes of the numeric type.
0.16
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
0.22
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
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
0.41
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
2.2
Mean skewness among attributes of the numeric type.
1.98
First quartile of standard deviation of attributes of the numeric type.
0.61
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.45
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
0.25
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
77.78
Percentage of instances belonging to the most frequent class.
2137.53
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
0.25
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.76
Entropy of the target attribute values.
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
28
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
6.24
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.16
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.61
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
-0.44
Minimum kurtosis among attributes of the numeric type.
16.31
Second quartile (Median) of means among attributes of the numeric type.
0.25
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.22
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
17.4
Maximum kurtosis among attributes of the numeric type.
0.14
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

14 tasks

508 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: defects
218 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: defects
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: defects
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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