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pc3

pc3

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  • mythbusting_1 OpenML-CC18 OpenML100 PROMISE study_1 study_123 study_14 study_15 study_20 study_34 study_41 study_52 study_7 study_98 study_99 study_225 study_236 study_293 study_253 study_388 study_388 study_388 study_388
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Author: Mike Chapman, NASA Source: [tera-PROMISE](http://openscience.us/repo/defect/mccabehalsted/pc3.html) - 2004 Please cite: Sayyad Shirabad, J. and Menzies, T.J. (2005) The PROMISE Repository of Software Engineering Databases. School of Information Technology and Engineering, University of Ottawa, Canada. PC3 Software defect prediction One of the NASA Metrics Data Program defect data sets. Data from flight software for earth orbiting satellite. Data comes from McCabe and Halstead features extractors of source code. These features were defined in the 70s in an attempt to objectively characterize code features that are associated with software quality. ### Relevant papers - Shepperd, M. and Qinbao Song and Zhongbin Sun and Mair, C. (2013) Data Quality: Some Comments on the NASA Software Defect Datasets, IEEE Transactions on Software Engineering, 39. - Tim Menzies and Justin S. Di Stefano (2004) How Good is Your Blind Spot Sampling Policy? 2004 IEEE Conference on High Assurance Software Engineering. - T. Menzies and J. DiStefano and A. Orrego and R. Chapman (2004) Assessing Predictors of Software Defects", Workshop on Predictive Software Models, Chicago

38 features

c (target)nominal2 unique values
0 missing
HALSTEAD_ERROR_ESTnumeric139 unique values
0 missing
HALSTEAD_EFFORTnumeric1329 unique values
0 missing
HALSTEAD_LENGTHnumeric357 unique values
0 missing
HALSTEAD_LEVELnumeric45 unique values
0 missing
HALSTEAD_PROG_TIMEnumeric1318 unique values
0 missing
HALSTEAD_VOLUMEnumeric1055 unique values
0 missing
MAINTENANCE_SEVERITYnumeric81 unique values
0 missing
MODIFIED_CONDITION_COUNTnumeric50 unique values
0 missing
MULTIPLE_CONDITION_COUNTnumeric68 unique values
0 missing
NODE_COUNTnumeric103 unique values
0 missing
NORMALIZED_CYLOMATIC_COMPLEXITYnumeric68 unique values
0 missing
NUM_OPERANDSnumeric227 unique values
0 missing
NUM_OPERATORSnumeric259 unique values
0 missing
NUM_UNIQUE_OPERANDSnumeric117 unique values
0 missing
NUM_UNIQUE_OPERATORSnumeric43 unique values
0 missing
NUMBER_OF_LINESnumeric170 unique values
0 missing
PERCENT_COMMENTSnumeric377 unique values
0 missing
LOC_TOTALnumeric123 unique values
0 missing
DESIGN_COMPLEXITYnumeric33 unique values
0 missing
BRANCH_COUNTnumeric72 unique values
0 missing
CALL_PAIRSnumeric20 unique values
0 missing
LOC_CODE_AND_COMMENTnumeric25 unique values
0 missing
LOC_COMMENTSnumeric58 unique values
0 missing
CONDITION_COUNTnumeric69 unique values
0 missing
CYCLOMATIC_COMPLEXITYnumeric52 unique values
0 missing
CYCLOMATIC_DENSITYnumeric77 unique values
0 missing
DECISION_COUNTnumeric45 unique values
0 missing
DECISION_DENSITYnumeric52 unique values
0 missing
LOC_BLANKnumeric54 unique values
0 missing
DESIGN_DENSITYnumeric78 unique values
0 missing
EDGE_COUNTnumeric126 unique values
0 missing
ESSENTIAL_COMPLEXITYnumeric25 unique values
0 missing
ESSENTIAL_DENSITYnumeric61 unique values
0 missing
LOC_EXECUTABLEnumeric118 unique values
0 missing
PARAMETER_COUNTnumeric8 unique values
0 missing
HALSTEAD_CONTENTnumeric1174 unique values
0 missing
HALSTEAD_DIFFICULTYnumeric822 unique values
0 missing
Show all 38 features

107 properties

NumberOfInstances
1563
Number of instances (rows) of the dataset.
NumberOfFeatures
38
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
37
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
AutoCorrelation
0.81
Average class difference between consecutive instances.
CfsSubsetEval_DecisionStumpAUC
0.5
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
0.1
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
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
0.5
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
0.1
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
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
0.5
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
0.1
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
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
0.48
Entropy of the target attribute values.
DecisionStumpAUC
0.71
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpErrRate
0.1
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
DecisionStumpKappa
0
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
Dimensionality
0.02
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
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.00001.Kappa
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
J48.0001.AUC
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.0001.Kappa
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
J48.001.AUC
0.53
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.ErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
J48.001.Kappa
0.12
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
MajorityClassPercentage
89.76
Percentage of instances belonging to the most frequent class.
MajorityClassSize
1403
Number of instances belonging to the most frequent class.
MaxAttributeEntropy
Maximum entropy among attributes.
MaxKurtosisOfNumericAtts
1039.34
Maximum kurtosis among attributes of the numeric type.
MaxMeansOfNumericAtts
34072.82
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
30.49
Maximum skewness among attributes of the numeric type.
MaxStdDevOfNumericAtts
358165.94
Maximum standard deviation of attributes of the numeric type.
MeanAttributeEntropy
Average entropy of the attributes.
MeanKurtosisOfNumericAtts
238.95
Mean kurtosis among attributes of the numeric type.
MeanMeansOfNumericAtts
1008.15
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
10.32
Mean skewness among attributes of the numeric type.
MeanStdDevOfNumericAtts
10334.5
Mean standard deviation of attributes of the numeric type.
MinAttributeEntropy
Minimal entropy among attributes.
MinKurtosisOfNumericAtts
-1.48
Minimum kurtosis among attributes of the numeric type.
MinMeansOfNumericAtts
0.12
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
-0.59
Minimum skewness among attributes of the numeric type.
MinStdDevOfNumericAtts
0.13
Minimum standard deviation of attributes of the numeric type.
MinorityClassPercentage
10.24
Percentage of instances belonging to the least frequent class.
MinorityClassSize
160
Number of instances belonging to the least frequent class.
NaiveBayesAUC
0.66
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesErrRate
0.48
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NaiveBayesKappa
0.07
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
NumberOfBinaryFeatures
1
Number of binary attributes.
PercentageOfBinaryFeatures
2.63
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
PercentageOfNumericFeatures
97.37
Percentage of numeric attributes.
PercentageOfSymbolicFeatures
2.63
Percentage of nominal attributes.
Quartile1AttributeEntropy
First quartile of entropy among attributes.
Quartile1KurtosisOfNumericAtts
9.98
First quartile of kurtosis among attributes of the numeric type.
Quartile1MeansOfNumericAtts
1.44
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
2.63
First quartile of skewness among attributes of the numeric type.
Quartile1StdDevOfNumericAtts
2.06
First quartile of standard deviation of attributes of the numeric type.
Quartile2AttributeEntropy
Second quartile (Median) of entropy among attributes.
Quartile2KurtosisOfNumericAtts
144.27
Second quartile (Median) of kurtosis among attributes of the numeric type.
Quartile2MeansOfNumericAtts
7.64
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
9.78
Second quartile (Median) of skewness among attributes of the numeric type.
Quartile2StdDevOfNumericAtts
15.93
Second quartile (Median) of standard deviation of attributes of the numeric type.
Quartile3AttributeEntropy
Third quartile of entropy among attributes.
Quartile3KurtosisOfNumericAtts
407.27
Third quartile of kurtosis among attributes of the numeric type.
Quartile3MeansOfNumericAtts
22.68
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
16.3
Third quartile of skewness among attributes of the numeric type.
Quartile3StdDevOfNumericAtts
43.86
Third quartile of standard deviation of attributes of the numeric type.
REPTreeDepth1AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1ErrRate
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth1Kappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
REPTreeDepth2AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2ErrRate
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth2Kappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
REPTreeDepth3AUC
0.75
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3ErrRate
0.11
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
REPTreeDepth3Kappa
0.11
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
RandomTreeDepth1AUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1ErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth1Kappa
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
RandomTreeDepth2AUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2ErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth2Kappa
0.17
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
RandomTreeDepth3AUC
0.59
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3ErrRate
0.16
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
RandomTreeDepth3Kappa
0.17
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
0.64
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NErrRate
0.12
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
kNN1NKappa
0.26
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Show all 107 properties

27 tasks

Supervised Classification on pc3
143129 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: c
Supervised Classification on pc3
193 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: c
Supervised Classification on pc3
0 runs - estimation_procedure: 33% Holdout set - target_feature: c
Supervised Classification on pc3
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: c
Supervised Classification on pc3
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: c
Learning Curve on pc3
86 runs - estimation_procedure: 10-fold Learning Curve - target_feature: c
Supervised Data Stream Classification on pc3
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: c
Clustering on pc3
0 runs - target_feature: c
Clustering on pc3
0 runs
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Clustering on pc3
0 runs - estimation_procedure: 50 times Clustering
Subgroup Discovery on pc3
1310 runs - target_feature: c
Subgroup Discovery on pc3
1308 runs - target_feature: c
Subgroup Discovery on pc3
0 runs - target_feature: c
Subgroup Discovery on pc3
0 runs - target_feature: c
Subgroup Discovery on pc3
0 runs - target_feature: c
Subgroup Discovery on pc3
0 runs - target_feature: c
Subgroup Discovery on pc3
0 runs - target_feature: c
Subgroup Discovery on pc3
0 runs - target_feature: c
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