Abstract: Machine learning is a powerful modelling approach that has applications in multiple industries. Advanced data analysis techniques, such as data mining, which place an emphasis on exploration and the creation of new insights, are becoming more and more effective tools for analysing the performance data of elite athletes and assisting in the crucial decision-making that is necessary to succeed. The aim is to enhance the precision of marathon running time prediction by leveraging data mining domains and machine learning. We introduce a model that utilizes performance analysis through data mining methods and employs regression techniques such as Linear Regression, Random Forest, K-nearest Neighbor, Support Vector Regression, and Decision Tree.

Keywords: Performance prediction, running, athletes, Smart watches, supervised machine learning algorithms.

PDF | DOI: 10.17148/IJARCCE.2023.12686

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