用于减少特征的改进型机器学习技术及其在垃圾邮件检测中的应用

IF 2.3 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent Information Systems Pub Date : 2024-08-07 DOI:10.1007/s10844-024-00870-z
Ahmed A. Ewees, Marwa A. Gaheen, Mohammed M. Alshahrani, Ahmed M. Anter, Fatma H. Ismail
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引用次数: 0

摘要

本文介绍了 MPAG,这是一种新的特征选择方法,旨在克服传统海洋捕食者算法(MPA)的局限性。MPA 在优化过程中可能会出现停滞并陷入局部最优状态。为了应对这一挑战,我们提出了一种改进版的 MPA,称为 MPAG,它结合了基于梯度的优化器 (GBO) 中的局部逃逸算子 (LEO)。通过利用 LEO 运算符,MPAG 增强了 MPA 的探索能力,尤其是在最初三分之一的迭代过程中。这种增强为种群注入了更多的多样性,从而改善了搜索空间的发现过程,降低了过早收敛的风险。我们在 14 个特征选择基准数据集上对 MPAG 的性能进行了评估,采用了七种性能指标,包括适配值、分类准确率和所选特征。我们的研究结果表明,在 86% 的数据集上,MPAG 的表现优于其他算法,这突出表明它有能力在各种数据集上选择最相关的特征,同时保持稳定性。此外,我们还利用两个网络安全应用(特别是垃圾邮件检测数据集)对 MPAG 进行了评估,结果表明 MPAG 在大多数性能指标上都优于其他方法。
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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Improved machine learning technique for feature reduction and its application in spam email detection

This paper introduces MPAG, a new feature selection method aimed at overcoming the limitations of the conventional Marine Predators Algorithm (MPA). The MPA may experience stagnation and become trapped in local optima during optimization. To address this challenge, we propose a refined version of the MPA, termed MPAG, which incorporates the Local Escape Operator (LEO) from the gradient-based optimizer (GBO). By leveraging the LEO operator, MPAG enhances the exploration ability of the MPA, particularly during the initial one-third of iterations. This enhancement injects more diversity into populations, thereby improving the process of search space discovery and mitigating the risk of premature convergence. The performance of MPAG is evaluated on 14 feature selection benchmark datasets, employing seven performance measures including fitness value, classification accuracy, and selected features. Our findings indicate that MPAG outperforms other algorithms in 86% of the datasets, underscoring its capability to select the most relevant features across various datasets while maintaining stability. Additionally, MPAG is evaluated using two cybersecurity applications, specifically spam detection datasets, where it demonstrates superior performance across most performance measures compared to other methods.

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来源期刊
Journal of Intelligent Information Systems
Journal of Intelligent Information Systems 工程技术-计算机:人工智能
CiteScore
7.20
自引率
11.80%
发文量
72
审稿时长
6-12 weeks
期刊介绍: The mission of the Journal of Intelligent Information Systems: Integrating Artifical Intelligence and Database Technologies is to foster and present research and development results focused on the integration of artificial intelligence and database technologies to create next generation information systems - Intelligent Information Systems. These new information systems embody knowledge that allows them to exhibit intelligent behavior, cooperate with users and other systems in problem solving, discovery, access, retrieval and manipulation of a wide variety of multimedia data and knowledge, and reason under uncertainty. Increasingly, knowledge-directed inference processes are being used to: discover knowledge from large data collections, provide cooperative support to users in complex query formulation and refinement, access, retrieve, store and manage large collections of multimedia data and knowledge, integrate information from multiple heterogeneous data and knowledge sources, and reason about information under uncertain conditions. Multimedia and hypermedia information systems now operate on a global scale over the Internet, and new tools and techniques are needed to manage these dynamic and evolving information spaces. The Journal of Intelligent Information Systems provides a forum wherein academics, researchers and practitioners may publish high-quality, original and state-of-the-art papers describing theoretical aspects, systems architectures, analysis and design tools and techniques, and implementation experiences in intelligent information systems. The categories of papers published by JIIS include: research papers, invited papters, meetings, workshop and conference annoucements and reports, survey and tutorial articles, and book reviews. Short articles describing open problems or their solutions are also welcome.
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