计算机硬件数据集

Data Set 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. Attribute Information: 1. 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) 2. Model Name: many unique symbols 3. MYCT: machine cycle time in nanoseconds (integer) 4. MMIN: minimum main memory in kilobytes (integer) 5. MMAX: maximum main memory in kilobytes (integer) 6. CACH: cache memory in kilobytes (integer) 7. CHMIN: minimum channels in units (integer) 8. CHMAX: maximum channels in units (integer) 9. PRP: published relative performance (integer) 10. ERP: estimated relative performance from the original article (integer) Relevant Papers: Ein-Dor and Feldmesser (CACM 4/87, pp 308-317) Kibler,D. & Aha,D. (1988). Instance-based Prediction of Real-Valued Attributes. In Proceedings of the CSCSI (Canadian AI) Conference. [Web link] Papers That Cite This Data Set1: Dan Pelleg. Scalable and Practical Probability Density Estimators for Scientific Anomaly Detection. School of Computer Science Carnegie Mellon University. 2004. [View Context]. Yongge Wang. A New Approach to Fitting Linear Models in High Dimensional Spaces. Alastair Scott (Department of Statistics, University of Auckland). [View Context]. Citation Request: Please refer to the Machine Learning Repository's citation policy Creator: 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) [phone]