The use of machine learning algorithms for the study of business profitability: a new approach based on preferences

J. Á. Domingo, P. L. Fernández, Antonio Bahamonde Rionda, J. Diaz
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引用次数: 1

Abstract

In recent years, researchers in the Field of Artificial Intelligence have developed a learning technique, namely, preference learning, that is suitable to be used for economic analysis. The present research empirically tests one of these models, which consists of a combination of LACE and RFE algorithms. The problem of forecasting the profitability of Spanish companies upon the basis of a set of financial ratios is used as a benchmark. The model provides forecasted rankings, which are a kind of information that is more useful for the economic analysts than the forecasted class memberships that traditional machine learning techniques provide.
利用机器学习算法研究商业盈利能力:一种基于偏好的新方法
近年来,人工智能领域的研究人员开发了一种适合用于经济分析的学习技术,即偏好学习。本研究对其中一个由LACE和RFE算法组成的模型进行了实证检验。在一组财务比率的基础上预测西班牙公司盈利能力的问题被用作基准。该模型提供预测排名,这是一种对经济分析师来说比传统机器学习技术提供的预测班级成员更有用的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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