Prediction of intel CPUs’ price with regression analysis

Research Article
Open access

Prediction of intel CPUs’ price with regression analysis

Dongrong Joe Fu 1*
  • 1 University of California San Diego    
  • *corresponding author dofu@ucsd.edu
Published on 8 December 2023 | https://doi.org/10.54254/2753-8818/19/20230562
TNS Vol.19
ISSN (Print): 2753-8826
ISSN (Online): 2753-8818
ISBN (Print): 978-1-83558-203-9
ISBN (Online): 978-1-83558-204-6

Abstract

CPU stands for the central processing unit. It is a unit that executes the instruction and allows the computer to run programs, making it an essential computer component. When people are looking for a new computer, either buying a built one or building one, CPU takes up a significant portion of the computer budget. The existence of Moore’s Law indicates that the CPUs’ price is predictable. This essay constructed the two models, multinomial linear regression and multivariable polynomial regression models, based on parts of Intel CPUs’ parameter value to predict their recommended sale price. According to the data set used in this research and the built model, the multinomial linear regression model is more accurate in predicting.

Keywords:

python, regression analysis, prediction, intel CPU.

Fu,D.J. (2023). Prediction of intel CPUs’ price with regression analysis. Theoretical and Natural Science,19,234-242.
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References

[1]. R. R. Schaller, “Moore’s law: past, present and future,” in IEEE Spectrum, vol. 34, no. 6, pp. 52-59, June 1997, doi: 10.1109/6.591665.

[2]. Yu, H., & Wu, J. (n.d.). (rep.). Real Estate Price Prediction with Regression and Classification.

[3]. Tang, F, Ishwaran, H. Random Forest Missing Data Algorithms. Stat Anal Data Min: The ASA Data Sci Journal. 2017; 10: 363– 377. https://doi.org/10.1002/sam.11348.


Cite this article

Fu,D.J. (2023). Prediction of intel CPUs’ price with regression analysis. Theoretical and Natural Science,19,234-242.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics

ISBN:978-1-83558-203-9(Print) / 978-1-83558-204-6(Online)
Editor:Marwan Omar, Roman Bauer
Conference website: https://www.confciap.org/
Conference date: 25 March 2023
Series: Theoretical and Natural Science
Volume number: Vol.19
ISSN:2753-8818(Print) / 2753-8826(Online)

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References

[1]. R. R. Schaller, “Moore’s law: past, present and future,” in IEEE Spectrum, vol. 34, no. 6, pp. 52-59, June 1997, doi: 10.1109/6.591665.

[2]. Yu, H., & Wu, J. (n.d.). (rep.). Real Estate Price Prediction with Regression and Classification.

[3]. Tang, F, Ishwaran, H. Random Forest Missing Data Algorithms. Stat Anal Data Min: The ASA Data Sci Journal. 2017; 10: 363– 377. https://doi.org/10.1002/sam.11348.