Published Paper Details:

This paper aims to predict the top-selling video game sales in North America between 1983 and 2016. The dataset is collected from an internet platform known as Kaggle.com. The dataset was generated by vgchartz.com. Exploitation the dataset, the RStudio IDE tool and R-programming language are used for data cleaning, analysis, and representation. The machine learning algorithm used in this project is linear regression. Based on the Video Games Sales knowledge, it would be fascinating to know what area unit the required factors that make a game further successfully sold-out than others in North America. So, we�d would like to research what quite video games that area unit further successfully sold-out in North America. We have a tendency to tend to jointly would like to point the results of this Analysis in Associate in nursing intuitive methodology by visualizing outcome victimization ggplot2 in R. In this project, we have a tendency to tend to require NA_Sales (North America sales) as response variable and specialize in operative predictions by analyzing the rest of variables inside the k video games sales data. The results can facilitate film companies to know the key of generating an advertisement success game.