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PC3

PC3

in_preparation ARFF Publicly available Visibility: public Uploaded 23-06-2017 by Kimberly Murphy
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software fault prediction

38 features

Class (target)nominal2 unique values
0 missing
V21numeric139 unique values
0 missing
V20numeric1329 unique values
0 missing
V22numeric357 unique values
0 missing
V23numeric45 unique values
0 missing
V24numeric1318 unique values
0 missing
V25numeric1055 unique values
0 missing
V26numeric81 unique values
0 missing
V27numeric50 unique values
0 missing
V28numeric68 unique values
0 missing
V29numeric103 unique values
0 missing
V30numeric68 unique values
0 missing
V31numeric227 unique values
0 missing
V32numeric259 unique values
0 missing
V33numeric117 unique values
0 missing
V34numeric43 unique values
0 missing
V35numeric170 unique values
0 missing
V36numeric377 unique values
0 missing
V37numeric123 unique values
0 missing
V11numeric33 unique values
0 missing
V2numeric72 unique values
0 missing
V3numeric20 unique values
0 missing
V4numeric25 unique values
0 missing
V5numeric58 unique values
0 missing
V6numeric69 unique values
0 missing
V7numeric52 unique values
0 missing
V8numeric77 unique values
0 missing
V9numeric45 unique values
0 missing
V10numeric51 unique values
0 missing
V1numeric54 unique values
0 missing
V12numeric78 unique values
0 missing
V13numeric126 unique values
0 missing
V14numeric25 unique values
0 missing
V15numeric61 unique values
0 missing
V16numeric118 unique values
0 missing
V17numeric8 unique values
0 missing
V18numeric1174 unique values
0 missing
V19numeric822 unique values
0 missing

62 properties

1563
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.
First quartile of mutual information between the nominal attributes and the target attribute.
2.63
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
97.37
Percentage of numeric attributes.
2.63
Percentage of nominal attributes.
First quartile of entropy among attributes.
12.55
First quartile of kurtosis among attributes of the numeric type.
1.73
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.
3.06
First quartile of skewness among attributes of the numeric type.
2.06
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
144.27
Second quartile (Median) of kurtosis among attributes of the numeric type.
7.64
Second quartile (Median) of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
9.78
Second quartile (Median) of skewness among attributes of the numeric type.
15.93
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
407.27
Third quartile of kurtosis among attributes of the numeric type.
22.68
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
16.3
Third quartile of skewness among attributes of the numeric type.
43.86
Third quartile of standard deviation of attributes of the numeric type.
0.86
Average class difference between consecutive instances.
1008.16
Mean of means among attributes of the numeric type.
0.48
Entropy of the target attribute values.
0.02
Number of attributes divided by the number of instances.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
89.76
Percentage of instances belonging to the most frequent class.
1403
Number of instances belonging to the most frequent class.
Maximum entropy among attributes.
1039.34
Maximum kurtosis among attributes of the numeric type.
34072.82
Maximum of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The maximum number of distinct values among attributes of the nominal type.
30.49
Maximum skewness among attributes of the numeric type.
358165.94
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
239.39
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
Average mutual information between the nominal attributes and the target attribute.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2
Average number of distinct values among the attributes of the nominal type.
10.44
Mean skewness among attributes of the numeric type.
10334.48
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
-1.48
Minimum kurtosis among attributes of the numeric type.
0.12
Minimum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
-0.46
Minimum skewness among attributes of the numeric type.
0.13
Minimum standard deviation of attributes of the numeric type.
10.24
Percentage of instances belonging to the least frequent class.
160
Number of instances belonging to the least frequent class.

12 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: area_under_roc_curve - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - 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
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task