CACTUS: a Comprehensive Abstraction and Classification Tool for Uncovering Structures

IF 7.2 4区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

ACM Transactions on Intelligent Systems and Technology Pub Date : 2024-02-27 DOI:10.1145/3649459

Luca Gherardini, Varun Ravi Varma, Karol Capała, Roger Woods, Jose Sousa

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引用次数: 0

Abstract

The availability of large data sets is providing the impetus for driving many current artificial intelligent developments. However, specific challenges arise in developing solutions that exploit small data sets, mainly due to practical and cost-effective deployment issues, as well as the opacity of deep learning models. To address this, the Comprehensive Abstraction and Classification Tool for Uncovering Structures (CACTUS) is presented as a means of improving secure analytics by effectively employing explainable artificial intelligence. CACTUS achieves this by providing additional support for categorical attributes, preserving their original meaning, optimising memory usage, and speeding up the computation through parallelisation. It exposes to the user the frequency of the attributes in each class and ranks them by their discriminative power. Performance is assessed by applying it to various domains, including Wisconsin Diagnostic Breast Cancer, Thyroid0387, Mushroom, Cleveland Heart Disease, and Adult Income data sets.

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CACTUS：用于揭示结构的综合抽象和分类工具

大型数据集的可用性为推动当前许多人工智能的发展提供了动力。然而，在开发利用小型数据集的解决方案时也遇到了一些具体挑战，主要是由于实际部署和成本效益问题，以及深度学习模型的不透明性。为了解决这个问题，我们提出了用于揭示结构的综合抽象和分类工具（CACTUS），作为通过有效利用可解释人工智能来改进安全分析的一种手段。CACTUS 通过为分类属性提供额外支持、保留其原始含义、优化内存使用以及通过并行化加快计算速度来实现这一目标。它向用户展示了每个类别中属性的频率，并根据其判别能力对它们进行排序。通过将其应用于各种领域，包括威斯康星诊断乳腺癌、甲状腺 0387、蘑菇、克利夫兰心脏病和成人收入数据集，对其性能进行了评估。

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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来源期刊

ACM Transactions on Intelligent Systems and Technology COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

9.30

自引率

2.00%

发文量

131

期刊介绍： ACM Transactions on Intelligent Systems and Technology is a scholarly journal that publishes the highest quality papers on intelligent systems, applicable algorithms and technology with a multi-disciplinary perspective. An intelligent system is one that uses artificial intelligence (AI) techniques to offer important services (e.g., as a component of a larger system) to allow integrated systems to perceive, reason, learn, and act intelligently in the real world. ACM TIST is published quarterly (six issues a year). Each issue has 8-11 regular papers, with around 20 published journal pages or 10,000 words per paper. Additional references, proofs, graphs or detailed experiment results can be submitted as a separate appendix, while excessively lengthy papers will be rejected automatically. Authors can include online-only appendices for additional content of their published papers and are encouraged to share their code and/or data with other readers.