在使用机器学习转换数据资产的同时创造商业价值

Ivana Dimitrovska, Toni Malinovski
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引用次数: 0

摘要

机器学习使计算机能够在没有特定编程的情况下从大量数据中学习。除了商业应用之外,公司开始认识到机器学习的重要性和可能性,以便将其数据资产转化为商业价值。本研究探讨了将机器学习集成到业务核心流程中,同时实现预测分析,从而增加业务价值并提供竞争优势。本文提出了一种基于回归分析的机器学习算法,用于马其顿大型企业公司的业务解决方案,同时预测给定业务输入阵列的实际价值结果。结果表明,大多数机器学习对所需流程输出的预测值偏离了实际员工决策的0%到15%。因此,它验证了所选方法的适当性,并具有在实践中有意义的预测准确性。作为商业环境中的机器学习案例研究,它包含有价值的信息,可以帮助公司理解机器学习对企业计算的重要性。它还指出了滥用机器学习的一些潜在陷阱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Creating a Business Value while Transforming Data Assets using Machine Learning
Machine learning enables computers to learn from large amounts of data without specific programming. Besides its commercial application, companies are starting to recognize machine learning importance and possibilities in order to transform their data assets into business value. This study explores integration of machine learning into business core processes, while enabling predictive analytics that can increase business values and provide competitive advantage. It proposes machine learning algorithm based on regression analysis for a business solution in large enterprise company in Macedonia, while predicting real-value outcome from a given array of business inputs. The results show that most of the machine learning predictive values for the desired process output deviated from 0 to 15% of actual employees' decision. Hence, it verifies the appropriateness of the chosen approach, with predictive accuracy that can be meaningful in practice. As a machine learning case study in business context, it contains valuable information that can help companies understand the significance of machine learning for enterprise computing. It also points out some potential pitfalls of machine learning misuse.
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