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cpu_act

cpu_act

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Author: Source: Unknown - Please cite: The Computer Activity databases are a collection of computer systems activity measures. The data was collected from a Sun Sparcstation 20/712 with 128 Mbytes of memory running in a multi-user university department. Users would typically be doing a large variety of tasks ranging from accessing the internet, editing files or running very cpu-bound programs. The data was collected continuously on two separate occasions. On both occassions, system activity was gathered every 5 seconds. The final dataset is taken from both occasions with equal numbers of observations coming from each collection epoch. System measures used: 1. lread - Reads (transfers per second ) between system memory and user memory. 2. lwrite - writes (transfers per second) between system memory and user memory. 3. scall - Number of system calls of all types per second. 4. sread - Number of system read calls per second. 5. swrite - Number of system write calls per second . 6. fork - Number of system fork calls per second. 7. exec - Number of system exec calls per second. 8. rchar - Number of characters transferred per second by system read calls. 9. wchar - Number of characters transfreed per second by system write calls. 10. pgout - Number of page out requests per second. 11. ppgout - Number of pages, paged out per second. 12. pgfree - Number of pages per second placed on the free list. 13. pgscan - Number of pages checked if they can be freed per second. 14. atch - Number of page attaches (satisfying a page fault by reclaiming a page in memory) per second. 15. pgin - Number of page-in requests per second. 16. ppgin - Number of pages paged in per second. 17. pflt - Number of page faults caused by protection errors (copy-on-writes). 18. vflt - Number of page faults caused by address translation. 19. runqsz - Process run queue size. 20. freemem - Number of memory pages available to user processes. 21. freeswap - Number of disk blocks available for page swapping. 22. usr - Portion of time (%) that cpus run in user mode. 23. sys - Portion of time (%) that cpus run in system mode. 24. wio - Portion of time (%) that cpus are idle waiting for block IO. 25. idle - Portion of time (%) that cpus are otherwise idle. The two different regression tasks obtained from these databases are: CompAct Predict usr, the portion of time that cpus run in user mode from all attributes 1-21. CompAct(s) Predict usr using a restricted number (excluding the paging information (10-18) Source: collection of regression datasets by Luis Torgo (ltorgo@ncc.up.pt) at http://www.ncc.up.pt/~ltorgo/Regression/DataSets.html Original source: DELVE repository of data. Characteristics: 8192 cases, 22 continuous attributes

22 features

usr (target)numeric56 unique values
0 missing
pgfreenumeric1070 unique values
0 missing
freeswapnumeric7658 unique values
0 missing
freememnumeric3165 unique values
0 missing
runqsznumeric302 unique values
0 missing
vfltnumeric3799 unique values
0 missing
pfltnumeric2987 unique values
0 missing
ppginnumeric1072 unique values
0 missing
pginnumeric832 unique values
0 missing
atchnumeric253 unique values
0 missing
pgscannumeric1202 unique values
0 missing
lreadnumeric235 unique values
0 missing
ppgoutnumeric774 unique values
0 missing
pgoutnumeric404 unique values
0 missing
wcharnumeric7939 unique values
0 missing
rcharnumeric7997 unique values
0 missing
execnumeric386 unique values
0 missing
forknumeric228 unique values
0 missing
swritenumeric640 unique values
0 missing
sreadnumeric794 unique values
0 missing
scallnumeric4115 unique values
0 missing
lwritenumeric189 unique values
0 missing

107 properties

8192
Number of instances (rows) of the dataset.
22
Number of attributes (columns) of the dataset.
0
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.
22
Number of numeric attributes.
0
Number of nominal attributes.
-14.02
Average class difference between consecutive instances.
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
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
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
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
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
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
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
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
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
Entropy of the target attribute values.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
0
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.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Maximum entropy among attributes.
618.08
Maximum kurtosis among attributes of the numeric type.
1328125.96
Maximum of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
The maximum number of distinct values among attributes of the nominal type.
21.54
Maximum skewness among attributes of the numeric type.
422019.43
Maximum standard deviation of attributes of the numeric type.
Average entropy of the attributes.
79.51
Mean kurtosis among attributes of the numeric type.
73907.63
Mean of means among attributes of the numeric type.
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.
Average number of distinct values among the attributes of the nominal type.
5
Mean skewness among attributes of the numeric type.
36701.76
Mean standard deviation of attributes of the numeric type.
Minimal entropy among attributes.
0.9
Minimum kurtosis among attributes of the numeric type.
1.13
Minimum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
The minimal number of distinct values among attributes of the nominal type.
-3.42
Minimum skewness among attributes of the numeric type.
2.48
Minimum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
100
Percentage of numeric attributes.
0
Percentage of nominal attributes.
First quartile of entropy among attributes.
4.89
First quartile of kurtosis among attributes of the numeric type.
7.7
First quartile of means among attributes of the numeric type.
First quartile of mutual information between the nominal attributes and the target attribute.
1.79
First quartile of skewness among attributes of the numeric type.
14.88
First quartile of standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
22.2
Second quartile (Median) of kurtosis among attributes of the numeric type.
20.58
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.
3.99
Second quartile (Median) of skewness among attributes of the numeric type.
62.25
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
59.86
Third quartile of kurtosis among attributes of the numeric type.
598.72
Third quartile of means among attributes of the numeric type.
Third quartile of mutual information between the nominal attributes and the target attribute.
5.55
Third quartile of skewness among attributes of the numeric type.
557.64
Third quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Standard deviation of the number of distinct values among attributes of the nominal type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk

7 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: usr
0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: usr
0 runs - estimation_procedure: Leave one out - target_feature: usr
0 runs - estimation_procedure: 10% Holdout set - target_feature: usr
0 runs - estimation_procedure: 33% Holdout set - target_feature: usr
0 runs - estimation_procedure: Test on Training Data - target_feature: usr
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: usr
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