Data
ar5

ar5

active ARFF Publicly available Visibility: public Uploaded 06-10-2014 by Joaquin Vanschoren
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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

108 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.
1
DataQuality extracted from Fantail Library
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.
NaN
Maximum mutual information between the nominal attributes and the target attribute.
-75.96
Minimum skewness among attributes of the numeric type.
3.33
Percentage of binary attributes.
NaN
Third quartile of entropy among attributes.
0.69
Average class difference between consecutive instances.
0.28
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
NaN
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
-1
The maximum number of distinct values among attributes of the nominal type.
0
DataQuality extracted from Fantail Library
0
Percentage of instances having missing values.
14.05
Third quartile of kurtosis 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
0.32
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
119.96
Maximum skewness among attributes of the numeric type.
0.22
Percentage of instances belonging to the least frequent class.
0
Percentage of missing values.
17.93
Third quartile of means among attributes of the numeric type.
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
0.69
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
21111483.87
DataQuality extracted from Fantail Library
8
Number of instances belonging to the least frequent class.
96.67
Percentage of numeric attributes.
NaN
Third quartile of mutual information between the nominal attributes and the target attribute.
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
0.28
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
-1
Average entropy of the attributes.
0.83
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
3.33
Percentage of nominal attributes.
3.61
DataQuality extracted from Fantail Library
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
0.32
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
81.35
Mean kurtosis among attributes of the numeric type.
0.17
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaN
First quartile of entropy among attributes.
20.78
DataQuality extracted from Fantail Library
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
0.69
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
-5283.51
Mean of means among attributes of the numeric type.
0.56
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-1.16
First quartile of kurtosis among attributes of the numeric type.
0.61
Area Under the ROC Curve 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
0.28
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
NaN
Average mutual information between the nominal attributes and the target attribute.
NaN
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
First quartile of means among attributes of the numeric type.
0.25
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
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
0.32
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
-1
Average number of distinct values among the attributes of the nominal type.
1
Number of binary attributes.
NaN
First quartile of mutual information between the nominal attributes and the target attribute.
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
-1
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
3.21
Mean skewness among attributes of the numeric type.
0.01
First quartile of skewness among 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
0.71
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
5584.79
Mean standard deviation of attributes of the numeric type.
0.32
DataQuality extracted from Fantail Library
0.25
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.76
Entropy of the target attribute values.
0.25
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
77.78
Percentage of instances belonging to the most frequent class.
NaN
Minimal entropy among attributes.
NaN
Second quartile (Median) of entropy among attributes.
0.16
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
0.72
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
0.36
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
28
Number of instances belonging to the most frequent class.
-2
Minimum kurtosis among attributes of the numeric type.
0.33
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.61
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.22
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
NaN
Maximum entropy among attributes.
-91638847.15
Minimum of means among attributes of the numeric type.
0.14
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
0.41
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
14389
Maximum kurtosis among attributes of the numeric type.
NaN
Minimal mutual information between the nominal attributes and the target attribute.
NaN
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
0.72
Second quartile (Median) of skewness among attributes of the numeric type.
0.16
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
0.78
The predictive accuracy obtained by always predicting the majority class.
26074559.21
Maximum of means among attributes of the numeric type.
-1
The minimal number of distinct values among attributes of the nominal type.

4 tasks

474 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
Define a new task

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