Classification Methods for MOBA Games

Abstract

The rise of the sports industry, which over time has increased in popularity along with machine learning and the possibilities for improving upon previously known and used methods, can serve many future predictions and benefits. This paper proposes a methodology to feature sorting in the context of supervised machine learning algorithms. A new perspective on machine learning by using it to predict outcomes with a database of the popular moba game Dota2, which consists of a large volume of data that was collected and analyzed. The reported results are concerned with three machine learning models with two significant metrics such as F-measure and Accuracy.