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Classification of Specialized Farms Applying Multivariate Statistical Methods

机译:应用多元统计方法对专业化农场进行分类

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Classification of specialized farms applying multivariate statistical methods The paper is aimed at application of advanced multivariate statistical methods when classifying cattle breeding farming enterprises by their economic size. Advantage of the model is its ability to use a few selected indicators compared to the complex methodology of current classification model that requires knowledge of detailed structure of the herd turnover and structure of cultivated crops. Output of the paper is intended to be applied within farm structure research focused on future development of Czech agriculture. As data source, the farming enterprises database for 2014 has been used, from the FADN CZ system. The predictive model proposed exploits knowledge of actual size classes of the farms tested. Outcomes of the linear discriminatory analysis multifactor classification method have supported the chance of filing farming enterprises in the group of Small farms (98 % filed correctly), and the Large and Very Large enterprises (100 % filed correctly). The Medium Size farms have been correctly filed at 58.11 % only. Partial shortages of the process presented have been found when discriminating Medium and Small farms.
机译:应用多元统计方法对专业农场进行分类本文旨在根据经济规模将先进的多元统计方法应用于牛养殖农场企业的分类。与当前分类模型的复杂方法相比,该模型的优势在于它能够使用一些选定的指标,而该分类方法需要了解牛群周转的详细结构和栽培作物的结构。本文的输出旨在用于关注捷克农业未来发展的农场结构研究中。作为数据源,使用了来自FADN CZ系统的2014年农业企业数据库。提出的预测模型利用了所测试农场的实际规模分类的知识。线性判别分析多因素分类方法的结果支持了在小型农场(正确提交98%),大型和超大型企业(正确提交100%)组中将农业企业归档的机会。中型服务器场的归档正确率仅为58.11%。在区分中型和小型农场时,发现所提出的过程有部分不足。

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