[1]YANG S X, HAN F, GUAN J. New gene selection method based on clustering and particle swarm optimization[J]. , 2013, 33(5):1285-1288.(杨善秀,韩飞,关健. 基于聚类和微粒群优化的基因选择新方法[J]. 计算机应用, 2013,33(5):1285-1288.)
[2]EIN-DOR L, KELA L, GETZ G, et al. Outcome signature genes in breast cancer: is there a unique set[J]. Bioinformatics, 2005, 21(2): 171-178.
[3]FAYYAD U M, WIERSE A, GRINSTEIN G G. Information visualization in data mining and knowledge discovery[M]. San Francisco: Morgan Kaufmann, 2002.
[4]SUN Y, FENG X, TANG J, et al. Survey on the research of multidimensional and multivariate data visualization[J]. Computer Science, 2008,35(11):1-7,59.(孙扬,封孝生,唐九阳,等. 多维可视化技术综述[J]. 计算机科学,2008,35(11):1-7,59.)
[5]WANG S, ZHU S. Neuralmechanism of visual information processing[J]. Chinese Ophthalmic Research, 2008, 26(9):717-720.(王淑珍,朱思泉.视觉信息加工的神经机制[J].眼科研究,2008,26(9):717-720.)
[6]KEIM D A. Information visualization and visual data mining[J]. Visualization and Computer Graphics, 2002, 8(1): 1-8.
[7]LIU K, ZHOU X, ZHOU D. Data visualization research and development[J]. Computer Engineering, 2002,28(8):1-2,63.(刘勘,周晓峥,周洞汝. 数据可视化的研究与发展[J]. 计算机工程,2002,28(8):1-2,63.)
[8]LI J, MARTENS J B, van WIJK J J. Judging correlation from scatterplots and parallel coordinate plots[J]. Information Visualization, 2010, 9(1): 13-30.
[9]LEI J, YANG J, ZHONG J, et al. High-dimensional data visualization based on principal component analysis and parallel coordinate[J]. Computer Engineering, 2011,37(1):48-50.(雷君虎,杨家红,钟坚成,等. 基于PCA和平行坐标的高维数据可视化[J]. 计算机工程,2011,37(1):48-50.)
[10]YUAN X, GUO P, XIAO H, et al. Scattering points in parallel coordinates[J]. IEEE Transactions on Visualization and Computer Graphics, 2009, 15(6): 1001-1008.
[11]GUO H, XIAO H, YUAN X. Multi-dimensional transfer function design based on flexible dimension projection embedded in parallel coordinates [C]// Proceedings of the 2011 IEEE Pacific Visualization Symposium (PacificVis). Piscataway: IEEE Press, 2011: 19-26.
[12]JOHANSSON J, TRELOAR R, JERN M. Integration of unsupervised clustering, interaction and parallel coordinates for the exploration of large multivariate data [C]// Proceedings of the 8th International Conference on Information Visualisation. Piscataway: IEEE Press, 2004: 52-57.
[13]YIN H. ViSOM — a novel method for multivariate data projection and structure visualization[J]. IEEE Transactions on Neural Networks, 2002, 13(1): 237-243.
[14]XU L, XU Y, CHOW T W S. PolSOM: a new method for multidimensional data visualization[J]. Pattern Recognition, 2010,43(4): 1668-1675.
[15]XU Y, XU L, CHOW T W S. PPoSOM: a new variant of PolSOM by using probabilistic assignment for multidimensional data visualization [J]. Neurocomputing, 2011, 74(11): 2018-2027.
[16]BREIMAN L. Random forests[J]. Machine Learning, 2001, 45(1): 5-32.
[17]FANG K, WU J, ZHU J, et al. A review of technologies on random forests[J]. Statistics and Information Forum, 2011,26(3):32-38. (方匡南,吴见彬,朱建平,等.随机森林方法研究综述[J]. 统计与信息论坛,2011,26(3):32-38.)
[18]QIU Y, MI H. Feature selection based on random forest and transductive inference[J]. Journal of Xiamen University: Natural Science, 2010, 49(3): 333-338.(邱一卉,米红. 基于随机森林和转导推理的特征提取方法[J]. 厦门大学学报:自然科学版,2010,49(3):333-338.)
[19]STATNIKOV A, ALIFERIS C F, TSAMARDINOS I, et al. A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis[J]. Bioinformatics, 2005, 21(5): 631-643.
[20]STATNIKOV A, TSAMARDINOS I, DOSBAYEV Y, et al. GEMS: a system for automated cancer diagnosis and biomarker discovery from microarray gene expression data[J]. International Journal of Medical informatics, 2005, 74(7): 491-503.
[21]GUYON I, LI J, MADER T, et al. Competitive baseline methods set new standards for the NIPS 2003 feature selection benchmark[J]. Pattern Recognition Letters, 2007, 28(12):1438-1444. |