Use of data mining algorithms in chicken breeding: A systematic review

Association Rule Mining and Data Mining - Recent Advances, New Perspectives and Applications [Working Title](2024)

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摘要
Data mining algorithms have been performed to reveal the factors that can be used to enhance live body weight and egg weight during chicken breeding. This work was conducted to systematically review the published articles on the use of data mining algorithms in chicken breeding. ScienceDirect, Web of Science, PubMed, Google Scholar and were used for searching articles. Using the combination of chicken or chicken breeding, data mining algorithm or decision tree, body weight and egg weight as keywords. The results indicated that 8 articles were included from 120 articles were found from searching. The 8 included articles were published from 2016 to 2021 and most of them were originated from South Africa (n = 3) followed by Turkey (n = 2) with. CHAID as the most used data mining algorithm (n = 5) followed by CART (n = 4). Out of 8 included articles, 6 of them used coefficient of determination (R2) as the selection criteria and CART was found as the best model followed by the CHAID model. It is concluded that CART followed by CHAID data mining algorithms are the recommended models that might be used for improving egg production and growth performance of chickens.
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