One of the domains of genetic enhancement that has extensively employed both simulation and authentic data is Biometrics. Selecting efficient models for the Genome-Wide Selection (GWS) process using molecular markers (SNPs) presents several challenges. Among these challenges is the effective identification of the optimal model for fitting a given dataset. To contribute to this endeavor, this paper's primary objective is to assess the predictive accuracy of nine (9) distinct models, each following different paradigms within the realm of Biometrics. The data employed in this study were generated through simulation, encompassing the primary issues encountered in this field of research, including high dimensionality, nonlinearity, and multicollinearity. As the primary findings, notable observations include the enhancement of predictive efficiency as data noise decreases, the predominance of the tree paradigm (for low noise levels, BOO), and the efficacy of the neural network paradigm (for high noise levels, RBF).

Patrick Wöhrle Guimaraes

Alcione de Paiva Oliveira

Cosme Damião Cruz

Acta Scientiarum Agronomy

该杂志发表农学所有领域的原创文章，包括土壤科学、农业昆虫学、土壤肥力和肥料、土壤物理学、栽培植物生理学、植物病理学、植物健康、植物技术、成因、形态和土壤分类、管理和保护土壤、植物病虫害综合治理、植物改良、农业微生物学、农业寄生虫学、种子生产和加工。

The journal "Acta Scientiarum - Agronomy" publishes original research articles in all fields of agronomy, including soil science, agricultural entomology, soil fertility and fertilization, soil physics, crop physiology, plant pathology, plant health, plant technology, soil genesis, morphology and classification, soil management and conservation, integrated pest management, plant breeding, agricultural microbiology, agricultural parasitology, and seed production and processing.

《Acta Scientiarum - Agronomy》杂志发表农学各个领域的原创研究文章，涵盖土壤科学、农业昆虫学、土壤肥力与施肥、土壤物理学、栽培植物生理学、植物病理学、植物健康、植物技术、土壤的成因、形态与分类、土壤管理与保护、植物病虫害综合治理、植物改良、农业微生物学、农业寄生虫学，以及种子生产与加工等主题。

Category	Quartile
农林科学	4
农林科学, 农艺学	4

Predictions in biometric models

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