Analysis of IPL Auction Dataset Using Explainable Machine Learning with Lime and H2O AutoML

Aradya Garg,Alka Chaudhary

2023 4th International Conference on Intelligent Engineering and Management (ICIEM)(2023)

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摘要
The global sports market, one of the biggest markets in the world, grew from $354.96 billion in 2021 to $496.52 billion in 2022, according to research from a business research organization. Sports teams are becoming increasingly devoted to investing in sports data analytics to gain a competitive edge as spending on the global sports market rises; as a result, it is predicted that the sports analytics industry will exceed $4.5 billion by 2025. It is the study of athletic performance and business health to maximize a sports organization's processes and results. Explainable machine learning (XML) is a key part of machine learning and AI because it explains how machine learning models create predictions. To establish trust and ensure accountability in AI systems, it is crucial to be able to comprehend and evaluate a model's predictions.
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关键词
Explainable Machine Learning,H20,LIME,R,Sports Analytics,Cricket,IPL,Stacked Ensemble
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