關(guān)聯(lián)分類算法的研究-文庫(kù)吧資料
2024-10-07 13:43本頁面
【正文】 n Proc. 2020 SIAM . on Data Mining (SDM39。 Engineering Systems (KES39。06), , Hong Kong, Oct 2020. [7] Abdelaziz Berrado, Gee C. Runger. Using Metarules to Organize and Group Discovered Association Rules. Data Mining and Knowledge Discover. 14: 409431, 2020. [8] F. Thabtah, P. Cowling, and Y. Peng. MCAR: Multiclass Classification based on Association Rule Approach. In Proceeding of the 3rd IEEE International Conference on Computer Systems and Applications. . Cairo, Egypt. Hebei University [9] O. R. Zaiane and . Antonie. On pruning and tuning rules for associative classifiers. In Proc. of Int39。01), , San Jose CA, Nov 2020. [4] J. Li, G. Dong, K. Ramamohanarao and L. Wong. DeEPs: A New InstanceBased Lazy Discovery and Classification System. Machine Learning. 54, , 2020. [5] Adriano Veloso, Wagner Meira Jr, and Mohammed J. Zaki. Lazy Association Classification. In Proc. of 2020 IEEE Int. Conf. on Data Mining (ICDM39。 ? 難度 ? 更新的計(jì)算量大 ? 采用更新，是否比以前的方法有效 Hebei University 研究過程可能遇到的困難及解決方案 ? 規(guī)則評(píng)價(jià)函數(shù)的確定 ? 不同數(shù)據(jù)庫(kù)的影響 ? 交疊現(xiàn)象對(duì)分類精度的影響 ? 選擇規(guī)則后，更新置信度和支持度 ? 比較不同交疊情況的分類精度 Hebei University 總結(jié) ? 針對(duì)關(guān)聯(lián)分類算法存在的問題 ? 算法的執(zhí)行效率 ? 剪枝的質(zhì)量和效率 ? 分類器的可理解性 Hebei University 參考文獻(xiàn) [1] B. Liu, W. Hsu and Y. Ma. Integrating Classification and Association Rule Mining. In Proc. of 1998 Int. Conf. on Knowledge Discovery and Data Mining (KDD39。()ACP r e d A c c RA???Hebei University ? R1: sup(R1) = 100, conf(R1) = 98% ? R2: sup(R2)
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