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Interval-valued test cost sensitive attribute reduction related to risk attitude

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Abstract

Attribute reduction is a typical topic in the field of rough sets. As an extension of this topic, test cost sensitive attribute reduction has garnered considerable attention in recent years, and scholars have made many achievements. However, existing research commonly operates under the assumption that test costs are exact values, disregarding the challenges associated with quantifying test costs accurately in certain real-world contexts. In light of the situation, this paper employs the form of interval values to represent the possible range of test costs and then studies the problem of attribute reduction based on interval-valued test costs. Firstly, a theoretical model for interval-valued test cost sensitive attribute reduction is constructed by utilizing a ranking method of intervals. In this model, some important concepts and properties are discussed. Especially, considering that the risk attitudes of different decision-makers may affect the decision results, an optimization problem related to risk attitude is formulated. Secondly, a backtracking algorithm and a heuristic algorithm are developed for tackling the optimization problem, along with the application of a competition strategy to enhance the heuristic algorithm’s performance. Finally, the performance of the two algorithms is evaluated on multiple UCI datasets, and comparisons are drawn with several state-of-the-art attribute reduction methods. Experimental analyses well illustrate the effectiveness and superiority of the suggested algorithms. It is hoped that this work provides new insights into cost sensitive attribute reduction from the perspective of cost uncertainty and provides a reference for decision-making problems.

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Data availability

The data on which the study is based was accessed from the UCI machine learning repository and is available for downloading through the following link https://archive.ics.uci.edu.

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Acknowledgements

This study is supported by the National Natural Science Foundation of China under Grant Nos. 12101289, 11871259 and 62076221, the Natural Science Foundation of Fujian Province under Grant No. 2022J01891, the Institute of Meteorological Big Data-Digital Fujian, and Fujian Key Laboratory of Data Science and Statistics (Minnan Normal University), China.

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Authors and Affiliations

  1. School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, 363000, China

    Yaqian Lu, Shujiao Liao, Wenyuan Yang & Di Wu

  2. Fujian Key Laboratory of Granular Computing and Application, Zhangzhou, 363000, China

    Yaqian Lu, Shujiao Liao, Wenyuan Yang & Ya’nan Guan

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  1. Yaqian Lu
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  2. Shujiao Liao
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Contributions

YQ.L. in charge of model creation, programming, algorithm implementation, the comprehensive analysis of the experimental data, and writing essays. SJ.L. formulates the overall research objectives, holds the direction of the research and provides technical guidance as well as project support for writing articles. WY.Y. provides guidance on essay writing. YN.G. is responsible for organizing and sorting out the experimental data. D.W. verifies the experimental results and visualizes them. All authors reviewed the manuscript.

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Correspondence to Shujiao Liao.

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Lu, Y., Liao, S., Yang, W. et al. Interval-valued test cost sensitive attribute reduction related to risk attitude. Int. J. Mach. Learn. & Cyber. (2024). https://doi.org/10.1007/s13042-024-02140-4

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