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- W2806258051 abstract "Data prediction have become a trend in today's business or organization. Thispaper is set to predict match outcomes for association football from the perspective of footballclub managers and coaches. This paper explored different data mining techniques used forpredicting the match outcomes where the target class is win, draw and lose. The main objectiveof this research is to find the most accurate data mining technique that fits the nature of footballdata. The techniques tested are Decision Trees, Neural Networks, Bayesian Network, and k-Nearest Neighbors. The results from the comparative experiments showed that Decision Treesproduced the highest average prediction accuracy in the domain of football match predictionby 99.56%." @default.
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- W2806258051 date "2018-05-01" @default.
- W2806258051 modified "2023-10-18" @default.
- W2806258051 title "A Comparative Study of Data Mining Techniques on Football Match Prediction" @default.
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- W2806258051 doi "https://doi.org/10.1088/1742-6596/1020/1/012003" @default.
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