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Outcome prediction of DOTA2 based on Naïve Bayes classifier

机译:基于朴素贝叶斯分类器的DOTA2效果预测

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Although DOTA2 is a popular game around the world, no clear algorithm or software are designed to forecast the winning probability by analyzing the lineups. However, the author finds that Naive Bayes classifier, one of the most common classification algorithm, can analyze the lineups and predict the outcome according to the lineups and gives an improved Naive Bayes classifier. Using the DOTA2 data set published in the UCI Machine Learning Repository, we test Naive Bayes classifier's prediction of respective winning probability of both sides in the game. The results show that Naive Bayes classifier is a practical tool to analyze the lineups and predict the outcome based on players' choices.
机译:尽管DOTA2在世界范围内都很流行,但没有明确的算法或软件可以通过分析阵容来预测获胜概率。然而,作者发现,最常见的分类算法之一,朴素贝叶斯分类器可以分析阵容并根据该阵容预测结果,并给出了一种改进的朴素贝叶斯分类器。使用UCI机器学习存储库中发布的DOTA2数据集,我们测试了朴素贝叶斯分类器对游戏中双方各自获胜概率的预测。结果表明,朴素贝叶斯分类器是一种实用的工具,可用于分析阵容并根据玩家的选择预测结果。

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