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hpc-job-scheduling

hpc-job-scheduling

in_preparation ARFF Publicly available Visibility: public Uploaded 03-11-2018 by Florian Pargent
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HPC Job Scheduling Data as included in the R-package 'AppliedPredictiveModeling' [Max Kuhn and Kjell Johnson (2018). AppliedPredictiveModeling: Functions and Data Sets for 'Applied Predictive Modeling'. R package version 1.1-7. https://CRAN.R-project.org/package=AppliedPredictiveModeling]. To obtain the dataset directly in R, call data(schedulingData, package = 'AppliedPredictiveModeling'). For a description of the dataset checkout the documentation of the R-package. The variable 'Class' was chosen as target variable.

8 features

Class (target)nominal4 unique values
0 missing
Protocolnominal14 unique values
0 missing
Compoundsnumeric858 unique values
0 missing
InputFieldsnumeric1730 unique values
0 missing
Iterationsnumeric11 unique values
0 missing
NumPendingnumeric303 unique values
0 missing
Hournumeric924 unique values
0 missing
Daynominal7 unique values
0 missing

62 properties

4331
Number of instances (rows) of the dataset.
8
Number of attributes (columns) of the dataset.
4
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.
5
Number of numeric attributes.
3
Number of nominal attributes.
1017.4
Third quartile of means among attributes of the numeric type.
0.33
Maximum mutual information between the nominal attributes and the target attribute.
4
The minimal number of distinct values among attributes of the nominal type.
62.5
Percentage of numeric attributes.
0.33
Third quartile of mutual information between the nominal attributes and the target attribute.
14
The maximum number of distinct values among attributes of the nominal type.
-0.55
Minimum skewness among attributes of the numeric type.
37.5
Percentage of nominal attributes.
8.15
Third quartile of skewness among attributes of the numeric type.
9.72
Maximum skewness among attributes of the numeric type.
3.98
Minimum standard deviation of attributes of the numeric type.
2.5
First quartile of entropy among attributes.
2335.12
Third quartile of standard deviation of attributes of the numeric type.
3650.08
Maximum standard deviation of attributes of the numeric type.
5.98
Percentage of instances belonging to the least frequent class.
8.14
First quartile of kurtosis among attributes of the numeric type.
5.13
Standard deviation of the number of distinct values among attributes of the nominal type.
2.93
Average entropy of the attributes.
259
Number of instances belonging to the least frequent class.
21.49
First quartile of means among attributes of the numeric type.
47.51
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
0.02
First quartile of mutual information between the nominal attributes and the target attribute.
426.23
Mean of means among attributes of the numeric type.
1.7
First quartile of skewness among attributes of the numeric type.
0.7
Average class difference between consecutive instances.
0.18
Average mutual information between the nominal attributes and the target attribute.
19.2
First quartile of standard deviation of attributes of the numeric type.
1.63
Entropy of the target attribute values.
15.68
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
2.93
Second quartile (Median) of entropy among attributes.
0
Number of attributes divided by the number of instances.
8.33
Average number of distinct values among the attributes of the nominal type.
51.98
Second quartile (Median) of kurtosis among attributes of the numeric type.
9.26
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
5.11
Mean skewness among attributes of the numeric type.
53.39
Second quartile (Median) of means among attributes of the numeric type.
51.05
Percentage of instances belonging to the most frequent class.
1012.92
Mean standard deviation of attributes of the numeric type.
0.18
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
2211
Number of instances belonging to the most frequent class.
2.5
Minimal entropy among attributes.
5.87
Second quartile (Median) of skewness among attributes of the numeric type.
3.36
Maximum entropy among attributes.
0.75
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
355.96
Second quartile (Median) of standard deviation of attributes of the numeric type.
3.36
Third quartile of entropy among attributes.
102.71
Maximum kurtosis among attributes of the numeric type.
13.73
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
84.64
Third quartile of kurtosis among attributes of the numeric type.
1537.06
Maximum of means among attributes of the numeric type.
0.02
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.

3 tasks

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