Machine Learning Algorithms Evaluation Methods by Utilizing R

H. Hamarashid, Shko M. Qader, Soran A. Saeed, B. Hassan, Nzar A. Ali
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引用次数: 1

Abstract

Machine Learning (ML) is a part of Artificial intelligence (AI) that designs and produces systems, which is capable of developing and learning from experiences automatically without making them programmable. ML concentrates on the computer program improvement, which has the ability to access and utilize data for learning from itself. There are different algorithms in ML field, but the most important questions that arise are: Which technique should be utilized on a dataset? and How to investigate ML algorithm? This paper presents the answer for the mentioned questions. Besides, investigation and checking algorithms for a data set will be addressed. In addition, it illustrates choosing the provided test options and metrics assessment. Finally, researchers will be able to conduct this research work on their datasets to select an appropriate model for their datasets.
基于R的机器学习算法评估方法
机器学习(ML)是人工智能(AI)的一部分,用于设计和生产系统,能够自动开发和学习经验,而无需将其编程。ML专注于计算机程序的改进,它具有访问和利用数据进行自我学习的能力。机器学习领域有不同的算法,但出现的最重要的问题是:应该在数据集上使用哪种技术?如何研究机器学习算法?本文给出了上述问题的答案。此外,还将讨论数据集的调查和检查算法。此外,它还说明了如何选择所提供的测试选项和度量评估。最后,研究人员将能够在他们的数据集上进行这项研究工作,为他们的数据集选择合适的模型。
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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