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首页> 外文期刊>Journal of Animal Science >BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Data to decisions
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BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Data to decisions

机译:大数据分析和精密动物农业研讨会:决策数据

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摘要

Big data are frequently used in many facets of business and agronomy to enhance knowledge needed to improve operational decisions. Livestock operations collect data of sufficient quantity to perform predictive analytics. Predictive analytics can be defined as a methodology and suite of data evaluation techniques to generate a prediction for specific target outcomes. The objective of this manuscript is to describe the process of using big data and the predictive analytic framework to create tools to drive decisions in livestock production, health, and welfare. The predictive analytic process involves selecting a target variable, managing the data, partitioning the data, then creating algorithms, refining algorithms, and finally comparing accuracy of the created classifiers. The partitioning of the datasets allows model building and refining to occur prior to testing the predictive accuracy of the model with naive data to evaluate overall accuracy. Many different classification algorithms are available for predictive use and testing multiple algorithms can lead to optimal results. Application of a systematic process for predictive analytics using data that is currently collected or that could be collected on livestock operations will facilitate precision animal management through enhanced livestock operational decisions.
机译:大数据经常用于商业和农学的许多方面,以提高改善运营决策所需的知识。牲畜操作收集足够数量的数据来执行预测分析。预测分析可以定义为数据评估技术的方法和套件,以生成针对特定目标结果的预测。该稿件的目标是描述使用大数据和预测分析框架的过程,以创建工具,以推动畜牧业生产,健康和福利的决策。预测分析过程涉及选择目标变量,管理数据,分区数据,然后创建算法,精炼算法,最后比较创建的分类器的准确性。数据集的分区允许在测试具有天真数据的模型的预测精度之前进行模型构建和精炼,以评估整体精度。许多不同的分类算法可用于预测性使用和测试多种算法可能导致最佳结果。使用当前收集的数据或可以在畜牧业务上收集的数据应用预测分析的系统过程将通过增强的牲畜操作决策促进精密动物管理。

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