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Data Mining and Machine Learning in Cricket Match Outcome Prediction: Missing Links

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dc.contributor.author Hatharasinghe, Manuka Maduranga
dc.contributor.author Poravi, Guhanathan
dc.date.accessioned 2020-05-24T08:17:07Z
dc.date.available 2020-05-24T08:17:07Z
dc.date.issued 2019
dc.identifier.citation Hatharasinghe, M M and Poravi, G (2019) ’Data Mining and Machine Learning in Cricket Match Outcome Prediction: Missing Links’ In:2019 IEEE 5th International Conference for Convergence in Technology (I2CT) Pune, India. 29 -31 March 2019. pp. 1-4. IEEE 10.1109/I2CT45611.2019.9033698 en_US
dc.identifier.uri https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9033698
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/409
dc.description.abstract Using Computer Intelligence to analyze and model the game of Cricket is a promising research area. The increased popularity and financial benefits have made Cricket an interesting sport to be subjected to statistical analysis and machine learning. The dynamic nature of Cricket, complex rules governing Cricket makes the task a challenging one. The various approaches taken and what has been disclosed from available work is neither very clear nor properly documented due to the differences in the approaches. If the good and the drawbacks of the existing work is properly analyzed and documented, it will assist in future researches. This paper presents an analysis of the existing work related to match outcome prediction in the Cricket domain. This paper is a result of an ongoing research, by the end of the research we hope to address the missing links and the drawbacks that will be explored in this paper. en_US
dc.subject Data Mining en_US
dc.subject Sabermetrics en_US
dc.subject Data models en_US
dc.subject Predictive models en_US
dc.title Data Mining and Machine Learning in Cricket Match Outcome Prediction: Missing Links en_US
dc.type Article en_US


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