Data

cpu_small

active
ARFF
Publicly available Visibility: public Uploaded 23-04-2014 by Jan van Rijn

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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)
Original source: DELVE repository of data.
Source: collection of regression datasets by Luis Torgo (ltorgo@ncc.up.pt) at
http://www.ncc.up.pt/~ltorgo/Regression/DataSets.html
Characteristics: 8192 cases, 13 continuous attributes

usr (target) | numeric | 56 unique values 0 missing | |

lread | numeric | 235 unique values 0 missing | |

lwrite | numeric | 189 unique values 0 missing | |

scall | numeric | 4115 unique values 0 missing | |

sread | numeric | 794 unique values 0 missing | |

swrite | numeric | 640 unique values 0 missing | |

fork | numeric | 228 unique values 0 missing | |

exec | numeric | 386 unique values 0 missing | |

rchar | numeric | 7997 unique values 0 missing | |

wchar | numeric | 7939 unique values 0 missing | |

runqsz | numeric | 302 unique values 0 missing | |

freemem | numeric | 3165 unique values 0 missing | |

freeswap | numeric | 7658 unique values 0 missing |

An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.

First quartile of mutual information between the nominal attributes and the target attribute.

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

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

Average number of distinct values among the attributes of the nominal type.

1.36

First quartile of skewness among attributes of the numeric type.

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

Standard deviation of the number of distinct values among attributes of the nominal type.

24.15

First quartile of standard deviation of attributes of the numeric type.

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2

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

19.42

Second quartile (Median) of kurtosis among attributes of the numeric type.

150.06

Second quartile (Median) of means among attributes of the numeric type.

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump

Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

Minimal mutual information between the nominal attributes and the target attribute.

3.85

Second quartile (Median) of skewness among attributes of the numeric type.

Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump

The minimal number of distinct values among attributes of the nominal type.

160.48

Second quartile (Median) of standard deviation of attributes of the numeric type.

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

Maximum mutual information between the nominal attributes and the target attribute.

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.

The maximum number of distinct values among attributes of the nominal type.

131.53

Third quartile of kurtosis among attributes of the numeric type.

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001

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

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

Third quartile of mutual information between the nominal attributes and the target attribute.

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

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

7.53

Third quartile of skewness among attributes of the numeric type.

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

Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001

3.83

First quartile of kurtosis among attributes of the numeric type.

71619.48

Third quartile of standard deviation of attributes of the numeric type.

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

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3

Average mutual information between the nominal attributes and the target attribute.

Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 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

Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3