[1] BRAY F, FERLAY J, SOERJOMATATRAM I, et al.Global cancer statistics 2018:globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J].CA Cancer Journal for Clinicians, 2018, 68(6):394-424. [2] 徐江峰, 谭玉龙.基于机器学习的HBase配置参数优化研究[J].计算机科学, 2020, 47(Z1):474-479. XU JF, TAN Y L.Research on HBase configuration parameter optimization based on machine learning[J].Computer Science, 2020, 47(Z1):474-479.(in Chinese) [3] PRSON G, ALOK J, TERO A, et al.Phenotypic screening combined with machine learning for efficient identification of breast cancer-selective therapeutic targets[J].Cell Chemical Biology, 2019, 26(7):970-979. [4] YUN L, KOHLBERGER T, MOHAMMAD D, et al.Artificial intelligence-based breast cancer nodal metastasis detection:insights into the black box for pathologists[J].Archives of Pathology & Laboratory Medicine, 2019, 143(7):859-868. [5] ZODWA D, FLAVIA Z, RODNEY H, et al.Artificial Intelligence (AI) and big data in cancer and precision oncology[J].Computational and Structural Biotechnology Journal, 2020, 18(8):2300-2311. [6] 方秋莲, 王培锦, 隋阳, 等.朴素Bayes分类器文本特征向量的参数优化[J].吉林大学学报(理学版), 2019, 240(6):1479-1484. FANG Q L, WANG P J, SUI Y, et al.Parameter optimization of text feature vector of naive Bayes classifier[J].Journal of Jilin University(Science Edition), 2019, 240(6):1479-1484.(in Chinese) [7] 张忠林, 曹婷婷.基于重采样与特征选择的不平衡数据分类算法[J].小型微型计算机系统, 2020, 41(6):1327-1333. ZHANG Z L, CAO T T.Unbalanced data classification algorithm based on resampling and feature selection[J].Journal of Chinese Mini-Micro Computer Systems, 2020, 41(6):1327-1333.(in Chinese) [8] CHEN G, LIU Y, GE Z Q.K-means bayes algorithm for imbalanced fault classification and big data application[J].Journal of Process Control, 2019, 81(3):54-64. [9] BI J J, ZHANG C S.An empirical comparison on state of the art multi-class imbalance learning algorithms and a new diversified ensemble learning scheme[J].Knowledge Based Systems, 2018, 158(6):81-93. [10] 薛铭龙, 李一博.基于改进随机森林算法的智能环境活动识别[J].计算机工程, 2019, 45(5):149-154. XUE M L, LI Y B.Intelligent environmental activity recognition based on improved random forest algorithm[J].Computer Engineering, 2019, 45(5):149-154.(in Chinese) [11] 王浩旻.基于代价敏感和集成学习的网络借贷信用评价方法与应用[D].成都:电子科技大学, 2020. WANG H M.Online lending credit evaluation method and application based on cost-sensitive and integrated learning[D].Chengdu:University of Electronic Science and Technology of China, 2020.(in Chinese) [12] UMI M, ISA I, ELLY M.Integrating data selection and extreme learning machine for imbalanced data[C]//Proceedings of 2015 International Conference on Computer Science and Computational Intelligence.Washington D.C., USA:IEEE Press, 2015:221-229. [13] MALGORZATA B, ALEKSANDRA W, MATEUSZ P.The proposal of undersampling method for learning from imbalanced datasets[J].Procedia Computer Science, 2019, 159(4):125-134. [14] NITESH V, CHAWLA B, KEVIN W, et al.SMOTE:synthetic minority over-sampling technique[J].Journal of Artificial Intelligence Research, 2002, 16(1):321-357. [15] HAN H, WANG W Y, MAO B H.Borderline-SMOTE:a new over-sampling method in imbalanced data sets learning[C]//Proceedings of International Conference on Advances in Intelligent Computing.Hefei, China:[s.n.], 2005:23-26. [16] 陈旭, 刘鹏鹤, 孙毓忠, 等.面向非平衡医学数据集的疾病预测模型研究[J].计算机学报, 2019, 42(3):596-609. CHEN X, LIU P H, SUN Y Z, et al.Research on disease prediction models for unbalanced medical data sets[J].Chinese Journal of Computers, 2019, 42(3):596-609.(in Chinese) [17] SARA F, SHAHROKH A, MICHAEL W.A comprehensive data level analysis for cancer diagnosis on imbalanced data[J].Journal of Biomedical Informatics, 2019, 90(9):78-89. [18] WANG K J, MAKOND B, CHEN K H, et al.A hybrid classifier combining SMOTE with PSO to estimate 5-year survivability of breast cancer patients[J].Applied Soft Computing, 2014, 20(1):15-24. [19] KUO R J, SU P Y, ZULVIA F E, et al.Integrating cluster analysis with granular computing for imbalanced data classification problem:a case study on prostate cancer prognosis[J].Computers and Industrial Engineering, 2018, 125(14):319-332. [20] WANG Q Y, ZHOU Y, ZHANG W M, et al.Adaptive sampling using self-paced learning for imbalanced cancer data pre-diagnosis[J].Expert Systems with Applications, 2020, 152(12):23-34. [21] RIVERA W A.Noise reduction a priori synthetic over-sampling for class imbalanced data sets(article)[J].Information Sciences, 2017, 408(4):146-161. [22] JIE L.Fuzzy support vector machine for imbalanced data with borderline noise[J].Fuzzy Sets and Systems, 2021, 413(5):64-73. [23] 章鸣嬛, 陈瑛, 汪城, 等.美国国立癌症研究所SEER数据库概述及应用[J].微型电脑应用, 2015, 31(12):26-28, 32. ZHANG M H, CHEN Y, WANG C, et al.Overview and application of SEER database of National Cancer Institute[J].Microcomputer Applications, 2015, 31(12):26-28, 32.(in Chinese) [24] WILSON D L.Asymptotic properties of nearest neighbor rules using edited data[J].IEEE Transactions on Systems, Man and Cybernetics, 1972, 31(2):408-421. [25] YU L, ZHOU R T, TANG L, et al.A DBN-based resampling SVM ensemble learning paradigm for credit classification with imbalanced data[J].Applied Soft Computing, 2018, 69(1):192-202. [26] 林智勇, 郝志峰, 杨晓伟.若干评价准则对不平衡数据学习的影响[J].华南理工大学学报(自然科学版), 2010, 38(4):147-155. LIN Z Y, HAO Z F, YANG X W.The influence of several evaluation criteria on unbalanced data learning[J].Journal of South China University of Technology (Natural Science Edition), 2010, 38(4):147-155.(in Chinese) |