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A machine learning strategy for predicting march madness winners

机译:预测3月疯狂获奖者的机器学习策略

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The Division I NCAA Men's Basketball Tournament is a popular sporting event held annually to determine the leagues National Champion. Over the past several years the betting scene surrounding the tournament has become arguably more popular than the tournament itself, drawing in fans who bet billions overall on its outcome. In this paper, we discuss the statistical challenges in correctly predicting winners in the tournament and present a machine learning strategy for predicting the games. The Kaggle Machine Learning March Mania Competition was used to test the effectiveness of the model by comparing it against other machine-learning-based models submitted to the competition. Overall, the project was considered successful as it scored in the top 15 percentile of all submissions.
机译:该司NCAA男子篮球锦标赛是一项受欢迎的体育赛事,每年举行,以确定联盟国家冠军。在过去的几年里,锦标赛周围的投注场景已经比锦标赛本身变得更加流行,在粉丝中绘制在其结果中投注数十亿的粉丝。在本文中,我们讨论了锦标赛中正确预测获奖者的统计挑战,并提出了一种预测游戏的机器学习策略。演奏机学习3月狂热的机器竞争用于通过将其与提交竞争对手的其他基于机器学习的模型进行比较来测试模型的有效性。总的来说,该项目被认为是成功的,因为它在所有提交的前15个百分位数中得分。

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