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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
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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

    	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 = "",
    	doi = "10.5120/ijais2019451823",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


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.


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