机器学习中相似性度量的预测能力评价

2020 24th International Conference on Information Technology (IT) Pub Date : 2020-02-01 DOI:10.1109/IT48810.2020.9070437

Igor Radisic, Sasa Lazarevic, I. Antović, Vojislav Stanojevic

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引用次数: 1

摘要

本文探讨了机器学习算法中使用的相似度量的预测能力。各种相似性度量的预测能力是基于它们在不同大小和属性的数据集上的应用和派生结果的评估来检查的。机器学习中的预测结果是许多不同机器学习算法的基础，本文的研究结果将阐明它们的预测能力有多好以及在哪些条件下。

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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Evaluation of Predictive Capabilities of Similarity Metrics in Machine Learning

This paper explores prediction capabilities of similarity metrics used in machine learning algorithms. Predictive capabilities of various similarity metrics are examined based on their application on data sets of varying sizes and properties and evaluation of derived results. Predicting outcomes in machine learning is fundamental to many different machine learning algorithms and the findings in this paper will clarify how good their predictive capabilities are and under which conditions.

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2020 24th International Conference on Information Technology (IT)

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