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Empirical analysis on sales of video games: a data mining approach

Aziz, Amar and Ismail, Shuhaida and Othman, Muhammad Fakri and Mustapha, Aida (2017) Empirical analysis on sales of video games: a data mining approach. In: International PostGraduate Conference on Applied Science & Physics 2017, 7 December 2017, Johor, Malaysia.

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Abstract

This paper studies factors that make the sales of video games becomes a blockbuster. The dataset used is collected from an online database maintained by VGChartz.com. Using the dataset, the Rapid Miner tool is used to select the features or factors and produce efficient estimation of the data. The techniques used in this project included the k- Nearest Neighbour (k-NN), Random Forest and Decision Tree. The factors and differences in the results are deliberated and discussed.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA297 Numerical analysis. Analysis
Divisions: Faculty of Applied Science and Technology > Department of Mathematics and Statistic
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 31 Jul 2019 01:00
Last Modified: 31 Jul 2019 01:00
URI: http://eprints.uthm.edu.my/id/eprint/11397
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