Prediction Analysis of Gaming Cost By Employing Data Mining Algorithms
Video games are a source of entertainment for different age groups. Players who are seeking quality video games spend more money on their systems. In this way they spend a hefty amount on internet, storage, GPU etc. Due to the addictive nature the cost is not negligible and there are not so many researches done on predicting the cost a player has to suffer. In this paper, the gaming cost is being determined by applying different algorithms. Data was collected from different age groups with different characteristics like the choice of storage options, game genres, internet speed and time they spend on games. Different models are being used like Ada boost, logistic regression, Decision tree and Random forest to check the accuracy of prediction analysis. This research will help in development of further models which can measure the gaming cost more accurately.
Ada boost, Decision tree, Graphics Processing Unit, Logistic regression, Random forest, Random Access Memory
MD. Rhineul Islam | Nakib Aman Turzo | Pritom Sarker Bishal