Summary

(No information yet)

License

unknown (from Weka repository)

Dependencies

Tags

arff slurped Weka

Attribute Types

Integer,String

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# Instances: 209 / # Attributes: 8
HDF5 (27.0 KB) XML CSV ARFF LibSVM Matlab Octave

Original Data Format

arff

Name

'cpu'

Version mldata

0

Comment

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Attributes 2 and 8 deleted.

As used by Kilpatrick, D. & Cameron-Jones, M. (1998). Numeric prediction using instance-based learning with encoding length selection. In Progress in Connectionist-Based Information Systems. Singapore: Springer-Verlag.

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

1. Title: Relative CPU Performance Data

2. Source Information -- Creators: Phillip Ein-Dor and Jacob Feldmesser -- Ein-Dor: Faculty of Management; Tel Aviv University; Ramat-Aviv; Tel Aviv, 69978; Israel -- Donor: David W. Aha (aha@ics.uci.edu) (714) 856-8779
   -- Date: October, 1987

3. Past Usage:

   1. Ein-Dor and Feldmesser (CACM 4/87, pp 308-317) -- Results: -- linear regression prediction of relative cpu performance -- Recorded 34% average deviation from actual values
   2. Kibler,D. & Aha,D. (1988). Instance-Based Prediction of Real-Valued Attributes. In Proceedings of the CSCSI (Canadian AI) Conference. -- Results: -- instance-based prediction of relative cpu performance -- similar results; no transformations required
   3. Predicted attribute: cpu relative performance (numeric)

4. Relevant Information: -- The estimated relative performance values were estimated by the authors using a linear regression method. See their article (pp 308-313) for more details on how the relative performance values were set.

5. Number of Instances: 209

6. Number of Attributes: 10 (6 predictive attributes, 2 non-predictive, 1 goal field, and the linear regression's guess)

7. Attribute Information:

8. vendor name: 30 (adviser, amdahl,apollo, basf, bti, burroughs, c.r.d, cambex, cdc, dec, dg, formation, four-phase, gould, honeywell, hp, ibm, ipl, magnuson, microdata, nas, ncr, nixdorf, perkin-elmer, prime, siemens, sperry, sratus, wang)

9. Model Name: many unique symbols

10. MYCT: machine cycle time in nanoseconds (integer)

11. MMIN: minimum main memory in kilobytes (integer)

12. MMAX: maximum main memory in kilobytes (integer)

13. CACH: cache memory in kilobytes (integer)

14. CHMIN: minimum channels in units (integer)

15. CHMAX: maximum channels in units (integer)

16. PRP: published relative performance (integer)

17. ERP: estimated relative performance from the original article (integer)

18. Missing Attribute Values: None

19. Class Distribution: the class value (PRP) is continuously valued. PRP Value Range: Number of Instances in Range: 0-20 31 21-100 121 101-200 27 201-300 13 301-400 7 401-500 4 501-600 2 above 600 4

Summary Statistics: Min Max Mean SD PRP Correlation MCYT: 17 1500 203.8 260.3 -0.3071 MMIN: 64 32000 2868.0 3878.7 0.7949 MMAX: 64 64000 11796.1 11726.6 0.8630 CACH: 0 256 25.2 40.6 0.6626 CHMIN: 0 52 4.7 6.8 0.6089 CHMAX: 0 176 18.2 26.0 0.6052 PRP: 6 1150 105.6 160.8 1.0000 ERP: 15 1238 99.3 154.8 0.9665

Names

vendor,MYCT,MMIN,MMAX,CACH,CHMIN,CHMAX,class,

Types

1. nominal:adviser,amdahl,apollo,basf,bti,burroughs,c.r.d,cdc,cambex,dec,dg,formation,four-phase,gould,hp,harris,honeywell,ibm,ipl,magnuson,microdata,nas,ncr,nixdorf,perkin-elmer,prime,siemens,sperry,sratus,wang
2. numeric
3. numeric
4. numeric
5. numeric
6. numeric
7. numeric
8. numeric

Data (first 10 data points)

vendor	MYCT	MMIN	MMAX	CACH	CHMIN	CHMAX	class
advi...	125	256	6000	256	16	128	199
amdahl	29	8000	32000	32	8	32	253
amdahl	29	8000	32000	32	8	32	253
amdahl	29	8000	32000	32	8	32	253
amdahl	29	8000	16000	32	8	16	132
amdahl	26	8000	32000	64	8	32	290
amdahl	23	16000	32000	64	16	32	381
amdahl	23	16000	32000	64	16	32	381
amdahl	23	16000	64000	64	16	32	749
amdahl	23	32000	64000	128	32	64	1238
...	...	...	...	...	...	...	...

Description

A gzip'ed tar containing UCI and UCI KDD datasets (uci-20070111.tar.gz, 17,952,832 Bytes)

URLs

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Publications

Data Source

http://www.ics.uci.edu/~mlearn/MLRepository.html http://kdd.ics.uci.edu/

Measurement Details

Usage Scenario

revision 1

by mldata on 2010-11-06 09:59

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