Data
PC4

PC4

in_preparation ARFF Publicly available Visibility: public Uploaded 23-08-2017 by Silvia Nunes
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software fault prediction data

38 features

Class (target)nominal2 unique values
0 missing
V1numeric54 unique values
0 missing
V2numeric61 unique values
0 missing
V3numeric22 unique values
0 missing
V4numeric36 unique values
0 missing
V5numeric57 unique values
0 missing
V6numeric41 unique values
0 missing
V7numeric43 unique values
0 missing
V8numeric70 unique values
0 missing
V9numeric23 unique values
0 missing
V10numeric47 unique values
0 missing
V11numeric31 unique values
0 missing
V12numeric76 unique values
0 missing
V13numeric105 unique values
0 missing
V14numeric25 unique values
0 missing
V15numeric59 unique values
0 missing
V16numeric107 unique values
0 missing
V17numeric8 unique values
0 missing
V18numeric1021 unique values
0 missing
V19numeric708 unique values
0 missing
V20numeric1165 unique values
0 missing
V21numeric120 unique values
0 missing
V22numeric336 unique values
0 missing
V23numeric40 unique values
0 missing
V24numeric1159 unique values
0 missing
V25numeric941 unique values
0 missing
V26numeric74 unique values
0 missing
V27numeric28 unique values
0 missing
V28numeric40 unique values
0 missing
V29numeric89 unique values
0 missing
V30numeric67 unique values
0 missing
V31numeric184 unique values
0 missing
V32numeric245 unique values
0 missing
V33numeric71 unique values
0 missing
V34numeric38 unique values
0 missing
V35numeric171 unique values
0 missing
V36numeric394 unique values
0 missing
V37numeric116 unique values
0 missing

62 properties

1458
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.
2.5
First quartile of skewness among attributes of the numeric type.
583.47
Mean of means among attributes of the numeric type.
2.02
First quartile of standard deviation of attributes of the numeric type.
0.89
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
0.54
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
48.05
Second quartile (Median) of kurtosis among attributes of the numeric type.
0.03
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
7
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
6.41
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
87.79
Percentage of instances belonging to the most frequent class.
1837.83
Mean standard deviation of attributes of the numeric type.
5.71
Second quartile (Median) of skewness among attributes of the numeric type.
1280
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
2.63
Percentage of binary attributes.
9.49
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.51
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
771.63
Maximum kurtosis among attributes of the numeric type.
0.11
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
173.88
Third quartile of kurtosis among attributes of the numeric type.
19505.52
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
97.37
Percentage of numeric attributes.
19.71
Third quartile of means among attributes of the numeric type.
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 nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
2
The maximum number of distinct values among attributes of the nominal type.
-0.46
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
9.49
Third quartile of skewness among attributes of the numeric type.
25.48
Maximum skewness among attributes of the numeric type.
0.12
Minimum standard deviation of attributes of the numeric type.
8.79
First quartile of kurtosis among attributes of the numeric type.
26.37
Third quartile of standard deviation of attributes of the numeric type.
62600.26
Maximum standard deviation of attributes of the numeric type.
12.21
Percentage of instances belonging to the least frequent class.
178
Number of instances belonging to the least frequent class.
1.49
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
104.87
Mean kurtosis among attributes of the numeric type.

9 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: area_under_roc_curve - target_feature: Class
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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