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Price Premiums Prediction using Classification and Regression Trees CART Algorithm in eBay Auctions

Mofareah Bin Mohamed, Mahmoud Kamel in Algorithms

International Journal of Applied Information Systems
Year of Publication: 2019
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Mofareah Bin Mohamed, Mahmoud Kamel
10.5120/ijais2019451823
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  1. Mofareah Bin Mohamed and Mahmoud Kamel. Price Premiums Prediction using Classification and Regression Trees (CART) Algorithm in eBay Auctions. International Journal of Applied Information Systems 12(24):17-22, October 2019. URL, DOI BibTeX

    @article{10.5120/ijais2019451823,
    	author = "Mofareah Bin Mohamed and Mahmoud Kamel",
    	title = "Price Premiums Prediction using Classification and Regression Trees (CART) Algorithm in eBay Auctions",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "October, 2019",
    	volume = 12,
    	number = 24,
    	month = "October",
    	year = 2019,
    	issn = "2249-0868",
    	pages = "17-22",
    	url = "http://www.ijais.org/archives/volume12/number24/1067-2019451823",
    	doi = "10.5120/ijais2019451823",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

Price premiums in internet auction are the percentage that the sale price exceeds or decreases the average price of this product, so, if the sale price exceeds the average price then the internet auction is price premiums otherwise it is non-price premiums.

The objective of the study is to analyze eBay auctions data using Classification and Regression Trees (CART), which is a type of decision trees induction. The information about previous auctions of a specific product was collected from the eBay site to the extent of its users and comprehensive, and the formulation of the previous information in the form of variables can be statistical operations on the processing of decision trees algorithms.

This study identifies the critical variables and ranks them according to their importance using the decision-making tree algorithms.

Reference

  1. Ueffing, N. 2018. Automatic Post-Editing and Machine Translation Quality Estimation at eBay. In Proceedings of the AMTA 2018 Workshop on Translation Quality Estimation and Automatic Post-Editing (pp. 1-34).
  2. Ba, S., & Pavlou, P. A. T2002. Evidence of the effect of trust building technology in electronic markets: Price premiums and buyer behavior. MIS quarterly, 247-248.
  3. Breiman, L., Friedman, J., Olshen, R., & Stone, C. 1984. Classification and regression trees. Belmont, CA: Wadsworth International Group.
  4. Cason, T. N., & Friedman, D. 2018. An empirical analysis of price formation in double auction markets. In The double auction market (pp. 253-284). Routledge.
  5. Liu, W. W., Liu, A., & Chan, G. H. 2018. Modeling eBay Price Using Stochastic Differential Equations. Journal of Forecasting.
  6. Hsu, S. B. 2013. Ordinary differential equations with applications (Vol. 21). World Scientific Publishing Company.
  7. Ghani, R. 2005. Price prediction and insurance for online auctions. In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining (pp. 411-418). ACM.
  8. Dass, M., Jank, W., &Shmueli, G. 2010. Dynamic price forecasting in simultaneous online art auctions. In Marketing Intelligent Systems using Soft Computing (pp. 417-445). Springer, Berlin, Heidelberg.
  9. Mullender Breiman L., Friedman J.H., Olshen R.A. and Stone C. J. 1984. Classification and Regression Trees (2nd Ed.). Pacific Grove, CA; Wadsworth.
  10. “E-Bay auctions datasets”, Internet: https://www.kaggle.com/onlineauctions/online-auctions-dataset/. Retrieved Feb 7, 2019.
  11. Kohavi, R. 1995. A study of cross-validation and bootstrap for accuracy estimation and model selection. In Ijcai (Vol. 14, No. 2, pp. 1137-1145).
  12. Baker, J., & Song, J. 2008. Exploring decision rules for sellers in business-to-consumer (b2c) internet auctions. International Journal of E-Business Research (IJEBR), 4(1), 1-21.?
  13. Dholakia, U. M. 2005. The usefulness of bidders’ reputation ratings to sellers in online auctions. Journal of Interactive Marketing, 19(1), 31-40.?
  14. Rodriguez, J. D., Perez, A., & Lozano, J. A. 2010. Sensitivity analysis of k-fold cross validation in prediction error estimation. IEEE transactions on pattern analysis and machine intelligence, 32(3), 569-575.?
  15. Murthy, S. K., & Salzberg, S. 1995. Decision Tree Induction: How Effective Is the Greedy Heuristic?. In KDD (pp. 222-227).?
  16. Brodley, C. E., & Utgoff, P. E. 1995. Multivariate decision trees. Machine learning, 19(1), 45-77.?
  17. Ince, H., &Trafalis, T. B. 2007. Kernel principal component analysis and support vector machines for stock price prediction. IIE Transactions, 39(6), 629-637.

Keywords

CART, Price premiums, eBay, K-fold-cross