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G3 Genes Genomes Genetics • Vol 15 • No 10
Bayesian divergence-based approach for genomic multitrait ordinal selection
2025
Abstract Effective genomic selection for ordinal traits, such as disease resistance scores, is a persistent challenge in plant breeding due to the discrete, ordered nature of these phenotypes. This study presents a novel Bayesian divergence-based framework fo…
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Machine Learning

Study of algorithms that improve automatically through experience

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalise to unseen data, and thus perform tasks without explicit instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance.

ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics.

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G3 Genes Genomes Genetics • Vol 15 • No 10
Bayesian divergence-based approach for genomic multitrait ordinal selection
2025
Abstract Effective genomic selection for ordinal traits, such as disease resistance scores, is a persistent challenge in plant breeding due to the discrete, ordered nature of these phenotypes. This study presents a novel Bayesian divergence-based framework for multitrait ordinal selection, implemented in the extended Multitrait Parental Selection R package (MPS-R). By leveraging decision-theoretic loss functions, including the Kullback–Leibler (KL) divergence, Bhattacharyya distance, and Hellinger distance, our ap…
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