Abstract
Granular-ball computing (GBC) proposed by Xia adaptively generates a different neighborhood for each object, resulting in greater generality and flexibility. Moreover, GBC greatly improves the efficiency by replacing point input with granular-ball. However, traditional granular-ball classifiers may lead to risky classification on uncertain cases. In this paper, we introduce three-way decision (3WD) into GBC to construct a novel three-way decision of granular-ball rough sets (3WD-GBRS) from the perspective of uncertainty. This helps to construct reasonable multi-granularity spaces for handling complex decision problems with uncertainty. 3WD-GBRS is constructed in a data-driven method based on fuzziness, which avoids the subjective definition of certain risk parameters when calculating the threshold pairs. We further analyze the fuzziness loss of multilevel decision result in 3WD-GBRS. Extensive comparative experiments are conducted with 3 state-of-the-art GB-based classifiers and 1 classical machine learning classifiers on 6 public benchmark datasets. The results show that 3WD-GBRS almost outperforms other comparison methods in term of effectiveness and efficiency.
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References
Zadeh, L.A.: Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst. 90(2), 111–127 (1997)
Pedrycz, W., Homenda, W.: Building the fundamentals of granular computing: a principle of justifiable granularity. Appl. Soft Comput. 13(10), 4209–4218 (2013)
Wang, G.Y., Yang, J., Xu, J.: Granular computing: from granularity optimization to multi-granularity joint problem solving. Granular Comput. 2, 105–120 (2017)
Yao, Y.Y.: Three-way granular computing, rough sets, and formal concept analysis. Int. J. Approximate Reasoning 116, 106–125 (2020)
Pawlak, Z.: Rough sets. Int. J. Comput. Inf. Sci. 11, 341–356 (1982)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)
Zhang, L., Zhang, B.: The quotient space theory of problem solving. Fund. Inform. 59(2–3), 287–298 (2004)
Hu, Q.H., Yu, D.R., Xie, Z.X.: Neighborhood classifiers. Expert Syst. Appl. 34(2), 866–876 (2008)
Fu, C., Yang, J.H.: Granular classification for imbalanced datasets: a Minkowski distance-based method. Algorithms 14(2), 54 (2021)
Xia, S.Y., Liu, Y.S., Ding, X., Wang, G.Y., Yu, H., Luo, Y.G.: Granular ball computing classifiers for efficient, scalable and robust learning. Inf. Sci. 483, 136–152 (2019)
Xia, S.Y., et al.: An efficient and accurate rough set for feature selection, classification, and knowledge representation. IEEE Trans. Knowl. Data Eng. 35(4), 5319–5331 (2024)
Xie, Q., et al.: GBG++: a fast and stable granular ball generation method for classification. IEEE Trans. Emerg. Top. Comput. Intell. 8(2), 2022–2036 (2024)
Chen, Y., Wang, P.X., Yang, X.B., Mi, J.S., Liu, D.: Granular ball guided selector for attribute reduction. Knowl.-Based Syst. 229, 107326 (2021)
Xia, S., Zhang, H., Li, W., Wang, G., Giem, E., Chen, Z.: GBNRS: a novel rough set algorithm for fast adaptive attribute reduction in classification. IEEE Trans. Knowl. Data Eng. 34(3), 1231–1242 (2020)
Yao, Y.Y.: The superiority of three-way decisions in probabilistic rough set models. Inf. Sci. 181(6), 1080–1096 (2011)
Yao, Y.Y.: Three-way decision and granular computing. Int. J. Approximate Reasoning 103, 107–123 (2018)
Chen, J., Chen, Y., He, Y., Xu, Y., Zhao, S., Zhang, Y.: A classified feature representation three-way decision model for sentiment analysis. Appl. Intell. 52, 7995–8007 (2021). https://doi.org/10.1007/s10489-021-02809-1
Yang, X., Li, T.R., Fujita, H., Liu, D., Yao, Y.Y.: A unified model of sequential three-way decisions and multilevel incremental processing. Knowl.-Based Syst. 134, 172–188 (2017)
Zhang, Q.H., Wang, J., Wang, G.Y.: The approximate representation of rough-fuzzy sets. Chin. J. Comput. Jisuanji Xuebao 38(7), 1484–1496 (2015)
Yang, J., Wang, X.Q., Wang, G.Y., Xia, D.Y.: Constructing three-way decision of rough fuzzy sets from the perspective of uncertainties. Cogn. Comput. 1–17 (2023)
Cheng, D.D., Li, Y., Xia, S.Y., Wang, G.Y., Huang, J.L., Zhang, S.L.: A fast granular-ball-based density peaks clustering algorithm for large-scale data. IEEE Trans. Neural Netw. Learn. Syst. (2023)
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This work was supported by the National Science Foundation of China (Grant number 62066049).
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Liu, Z., Xu, T., Yang, J., Xia, S. (2024). Three-Way Decision of Granular-Ball Rough Sets Based on Fuzziness. In: Hu, M., Cornelis, C., Zhang, Y., Lingras, P., Ślęzak, D., Yao, J. (eds) Rough Sets. IJCRS 2024. Lecture Notes in Computer Science(), vol 14840. Springer, Cham. https://doi.org/10.1007/978-3-031-65668-2_3
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