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Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data

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  1. Youssef Anzarmou & Abdallah Mkhadri & Karim Oualkacha, 2023. "Sparse overlapped linear discriminant analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 388-417, March.
  2. Makoto Aoshima & Kazuyoshi Yata, 2019. "Distance-based classifier by data transformation for high-dimension, strongly spiked eigenvalue models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(3), pages 473-503, June.
  3. Boulesteix, Anne-Laure & Tutz, Gerhard, 2006. "Identification of interaction patterns and classification with applications to microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 783-802, February.
  4. Chakraborty, Sounak, 2009. "Simultaneous cancer classification and gene selection with Bayesian nearest neighbor method: An integrated approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1462-1474, February.
  5. Jianqing Fan & Yang Feng & Jiancheng Jiang & Xin Tong, 2016. "Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 275-287, March.
  6. Dettling, Marcel & Bühlmann, Peter, 2004. "Finding predictive gene groups from microarray data," Journal of Multivariate Analysis, Elsevier, vol. 90(1), pages 106-131, July.
  7. M. Ballings & D. Van Den Poel & E. Verhagen, 2013. "Evaluating the Added Value of Pictorial Data for Customer Churn Prediction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/869, Ghent University, Faculty of Economics and Business Administration.
  8. Novoselova Natalia & Tom Igor & Borisov Arkady & Polaka Inese, 2013. "Feature Ranking by Classification Accuracy Estimation of Multiple Data Samples," Information Technology and Management Science, Sciendo, vol. 16(1), pages 95-100, December.
  9. Matthias Bogaert & Michel Ballings & Martijn Hosten & Dirk Van den Poel, 2017. "Identifying Soccer Players on Facebook Through Predictive Analytics," Decision Analysis, INFORMS, vol. 14(4), pages 274-297, December.
  10. Wang, Tao & Zhu, Lixing, 2013. "Sparse sufficient dimension reduction using optimal scoring," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 223-232.
  11. Shaheena Bashir & Edward Carter, 2010. "Penalized multinomial mixture logit model," Computational Statistics, Springer, vol. 25(1), pages 121-141, March.
  12. Ishii, Aki & Yata, Kazuyoshi & Aoshima, Makoto, 2022. "Geometric classifiers for high-dimensional noisy data," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
  13. Kanisha Shah & Shanaya Patel & Sheefa Mirza & Rakesh M Rawal, 2018. "A multi-gene expression profile panel for predicting liver metastasis: An algorithmic approach," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-14, November.
  14. Lambert-Lacroix, Sophie & Peyre, Julie, 2006. "Local likelihood regression in generalized linear single-index models with applications to microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 2091-2113, December.
  15. Hall, Peter & Xue, Jing-Hao, 2014. "On selecting interacting features from high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 694-708.
  16. Khalili, Abbas & Huang, Tim & Lin, Shili, 2009. "A robust unified approach to analyzing methylation and gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1701-1710, March.
  17. Guan-Hua Huang & Su-Mei Wang & Chung-Chu Hsu, 2011. "Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 584-611, October.
  18. Kubokawa, Tatsuya & Srivastava, Muni S., 2008. "Estimation of the precision matrix of a singular Wishart distribution and its application in high-dimensional data," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 1906-1928, October.
  19. Rossell David & Guerra Rudy & Scott Clayton, 2008. "Semi-Parametric Differential Expression Analysis via Partial Mixture Estimation," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-29, April.
  20. Lian, Heng, 2010. "Sparse Bayesian hierarchical modeling of high-dimensional clustering problems," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1728-1737, August.
  21. M. Kathleen Kerr, 2003. "Design Considerations for Efficient and Effective Microarray Studies," Biometrics, The International Biometric Society, vol. 59(4), pages 822-828, December.
  22. Nguyen, Danh V. & Rocke, D.M.David M., 2004. "On partial least squares dimension reduction for microarray-based classification: a simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 46(3), pages 407-425, June.
  23. Lee, Jae Won & Lee, Jung Bok & Park, Mira & Song, Seuck Heun, 2005. "An extensive comparison of recent classification tools applied to microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 869-885, April.
  24. Márton Gosztonyi & Csákné Filep Judit, 2022. "Profiling (Non-)Nascent Entrepreneurs in Hungary Based on Machine Learning Approaches," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
  25. Wang, Tao & Xu, Pei-Rong & Zhu, Li-Xing, 2012. "Non-convex penalized estimation in high-dimensional models with single-index structure," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 221-235.
  26. Hung-Chia Chen & Wen Zou & Tzu-Pin Lu & James J Chen, 2014. "A Composite Model for Subgroup Identification and Prediction via Bicluster Analysis," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-14, October.
  27. Jansen, Nora & Hinz, Oliver & Deusser, Clemens & Strufe, Thorsten, 2021. "Is the Buzz on? – A Buzz Detection System for Viral Posts in Social Media," Journal of Interactive Marketing, Elsevier, vol. 56(C), pages 1-17.
  28. Makoto Aoshima & Kazuyoshi Yata, 2014. "A distance-based, misclassification rate adjusted classifier for multiclass, high-dimensional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(5), pages 983-1010, October.
  29. Park, Junyong & Park, DoHwan, 2015. "Stein’s method in high dimensional classification and applications," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 110-125.
  30. Xu, Kai & Hao, Xinxin, 2019. "A nonparametric test for block-diagonal covariance structure in high dimension and small samples," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 551-567.
  31. Irina Gaynanova & James G. Booth & Martin T. Wells, 2016. "Simultaneous Sparse Estimation of Canonical Vectors in the ≫ Setting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 696-706, April.
  32. Mingue Sun, 2009. "Liquidity Risk and Financial Competition: A Mixed Integer Programming Model for Multiple-Class Discriminant Analysis," Working Papers 0102, College of Business, University of Texas at San Antonio.
  33. Hossain, Ahmed & Beyene, Joseph & Willan, Andrew R. & Hu, Pingzhao, 2009. "A flexible approximate likelihood ratio test for detecting differential expression in microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3685-3695, August.
  34. John Ormerod & M. Wand & Inge Koch, 2008. "Penalised spline support vector classifiers: computational issues," Computational Statistics, Springer, vol. 23(4), pages 623-641, October.
  35. Luca Scrucca, 2014. "Graphical tools for model-based mixture discriminant analysis," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(2), pages 147-165, June.
  36. B. Larivière & D. Van Den Poel, 2004. "Predicting Customer Retention and Profitability by Using Random Forests and Regression Forests Techniques," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/282, Ghent University, Faculty of Economics and Business Administration.
  37. Giuseppe Jurman & Samantha Riccadonna & Roberto Visintainer & Cesare Furlanello, 2012. "Algebraic Comparison of Partial Lists in Bioinformatics," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-20, May.
  38. Scrucca, Luca, 2007. "Class prediction and gene selection for DNA microarrays using regularized sliced inverse regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 438-451, September.
  39. A. Poterie & J.-F. Dupuy & V. Monbet & L. Rouvière, 2019. "Classification tree algorithm for grouped variables," Computational Statistics, Springer, vol. 34(4), pages 1613-1648, December.
  40. Wang, Cheng & Tong, Tiejun & Cao, Longbing & Miao, Baiqi, 2014. "Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 222-232.
  41. Buckinx, Wouter & Van den Poel, Dirk, 2005. "Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting," European Journal of Operational Research, Elsevier, vol. 164(1), pages 252-268, July.
  42. Fraiman, Ricardo & Justel, Ana & Svarc, Marcela, 2010. "Pattern recognition via projection-based kNN rules," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1390-1403, May.
  43. Ahn, Hongshik & Moon, Hojin & Fazzari, Melissa J. & Lim, Noha & Chen, James J. & Kodell, Ralph L., 2007. "Classification by ensembles from random partitions of high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6166-6179, August.
  44. Wang, Cheng & Cao, Longbing & Miao, Baiqi, 2013. "Optimal feature selection for sparse linear discriminant analysis and its applications in gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 140-149.
  45. Yang, Tae Young, 2009. "Simple Bayesian binary framework for discovering significant genes and classifying cancer diagnosis," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1743-1754, March.
  46. Tutz, Gerhard & Ramzan, Shahla, 2015. "Improved methods for the imputation of missing data by nearest neighbor methods," Computational Statistics & Data Analysis, Elsevier, vol. 90(C), pages 84-99.
  47. Ali E. Abbas & Susan P. Holmes, 2004. "Bioinformatics and Management Science: Some Common Tools and Techniques," Operations Research, INFORMS, vol. 52(2), pages 165-190, April.
  48. Yuk Yee Leung & Chun Qi Chang & Yeung Sam Hung, 2012. "An Integrated Approach for Identifying Wrongly Labelled Samples When Performing Classification in Microarray Data," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-10, October.
  49. Hothorn, Torsten & Lausen, Berthold, 2005. "Bundling classifiers by bagging trees," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 1068-1078, June.
  50. Pittelkow Yvonne E & Wilson Susan R, 2003. "Visualisation of Gene Expression Data - the GE-biplot, the Chip-plot and the Gene-plot," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 2(1), pages 1-19, September.
  51. Chakraborty, Sounak, 2009. "Bayesian binary kernel probit model for microarray based cancer classification and gene selection," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4198-4209, October.
  52. Maharaj, Elizabeth A. & Alonso, Andres M., 2007. "Discrimination of locally stationary time series using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 879-895, October.
  53. Asuman Turkmen & Nedret Billor, 2013. "Partial least squares classification for high dimensional data using the PCOUT algorithm," Computational Statistics, Springer, vol. 28(2), pages 771-788, April.
  54. Tomohiro Ando & Sadanori Konishi, 2009. "Nonlinear logistic discrimination via regularized radial basis functions for classifying high-dimensional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(2), pages 331-353, June.
  55. Debashis Ghosh, 2003. "Penalized Discriminant Methods for the Classification of Tumors from Gene Expression Data," Biometrics, The International Biometric Society, vol. 59(4), pages 992-1000, December.
  56. Guo Yu & Balasubramanian Raji, 2012. "Comparative Evaluation of Classifiers in the Presence of Statistical Interactions between Features in High Dimensional Data Settings," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-32, June.
  57. Masashi Hyodo & Takahiro Nishiyama, 2018. "A simultaneous testing of the mean vector and the covariance matrix among two populations for high-dimensional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 680-699, September.
  58. Federica Rizzi & Lucia Belloni & Pellegrino Crafa & Mirca Lazzaretti & Daniel Remondini & Stefania Ferretti & Piero Cortellini & Arnaldo Corti & Saverio Bettuzzi, 2008. "A Novel Gene Signature for Molecular Diagnosis of Human Prostate Cancer by RT-qPCR," PLOS ONE, Public Library of Science, vol. 3(10), pages 1-9, October.
  59. Peter Bickel & Bo Li & Alexandre Tsybakov & Sara Geer & Bin Yu & Teófilo Valdés & Carlos Rivero & Jianqing Fan & Aad Vaart, 2006. "Regularization in statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(2), pages 271-344, September.
  60. Ahn, Jeongyoun & Jeon, Yongho, 2015. "Sparse HDLSS discrimination with constrained data piling," Computational Statistics & Data Analysis, Elsevier, vol. 90(C), pages 74-83.
  61. Brendan P. W. Ames & Mingyi Hong, 2016. "Alternating direction method of multipliers for penalized zero-variance discriminant analysis," Computational Optimization and Applications, Springer, vol. 64(3), pages 725-754, July.
  62. Anindya Bhadra & Jyotishka Datta & Nicholas G. Polson & Brandon T. Willard, 2021. "The Horseshoe-Like Regularization for Feature Subset Selection," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 185-214, May.
  63. Chételat, Didier & Wells, Martin T., 2016. "Improved second order estimation in the singular multivariate normal model," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 1-19.
  64. Ballings, Michel & Van den Poel, Dirk & Bogaert, Matthias, 2016. "Social media optimization: Identifying an optimal strategy for increasing network size on Facebook," Omega, Elsevier, vol. 59(PA), pages 15-25.
  65. Kasim Adetayo & Lin Dan & Van Sanden Suzy & Clevert Djork-Arné & Bijnens Luc & Göhlmann Hinrich & Amaratunga Dhammika & Hochreiter Sepp & Shkedy Ziv & Talloen Willem, 2010. "Informative or Noninformative Calls for Gene Expression: A Latent Variable Approach," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-31, January.
  66. Shieh Albert D & Hung Yeung Sam, 2009. "Detecting Outlier Samples in Microarray Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-26, February.
  67. Fisher, Thomas J. & Sun, Xiaoqian & Gallagher, Colin M., 2010. "A new test for sphericity of the covariance matrix for high dimensional data," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2554-2570, November.
  68. Zhang, Chunming & Fu, Haoda & Jiang, Yuan & Yu, Tao, 2007. "High-dimensional pseudo-logistic regression and classification with applications to gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 452-470, September.
  69. Xiao-Lei Xia & Huanlai Xing & Xueqin Liu, 2013. "Analyzing Kernel Matrices for the Identification of Differentially Expressed Genes," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-19, December.
  70. Kim, Yongdai & Kwon, Sunghoon & Heun Song, Seuck, 2006. "Multiclass sparse logistic regression for classification of multiple cancer types using gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1643-1655, December.
  71. Srivastava, Muni S. & Du, Meng, 2008. "A test for the mean vector with fewer observations than the dimension," Journal of Multivariate Analysis, Elsevier, vol. 99(3), pages 386-402, March.
  72. Long Feng & Changliang Zou & Zhaojun Wang, 2016. "Multivariate-Sign-Based High-Dimensional Tests for the Two-Sample Location Problem," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 721-735, April.
  73. Rauf Ahmad, M. & Pavlenko, Tatjana, 2018. "A U-classifier for high-dimensional data under non-normality," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 269-283.
  74. Vera Miguéis & Dirk Poel & Ana Camanho & João Falcão e Cunha, 2012. "Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(4), pages 337-353, December.
  75. Takayuki Yamada & Tetsuto Himeno, 2019. "Estimation of multivariate 3rd moment for high-dimensional data and its application for testing multivariate normality," Computational Statistics, Springer, vol. 34(2), pages 911-941, June.
  76. Jörnsten, Rebecka, 2004. "Clustering and classification based on the L1 data depth," Journal of Multivariate Analysis, Elsevier, vol. 90(1), pages 67-89, July.
  77. Wu, Tong Tong & He, Xin, 2012. "Coordinate ascent for penalized semiparametric regression on high-dimensional panel count data," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 25-33, January.
  78. Schott, James R., 2007. "A test for the equality of covariance matrices when the dimension is large relative to the sample sizes," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6535-6542, August.
  79. Jiayu Lai & Xiaoyi Wang & Kaige Zhao & Shurong Zheng, 2023. "Block-diagonal test for high-dimensional covariance matrices," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 447-466, March.
  80. Anne-Laure Boulesteix & Robert Hable & Sabine Lauer & Manuel J. A. Eugster, 2015. "A Statistical Framework for Hypothesis Testing in Real Data Comparison Studies," The American Statistician, Taylor & Francis Journals, vol. 69(3), pages 201-212, August.
  81. Gaynanova, Irina & Wang, Tianying, 2019. "Sparse quadratic classification rules via linear dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 278-299.
  82. Pedro Duarte Silva, 2009. "LINEAR DISCRIMINANT RULES for HIGH-DIMENSIONAL CORRELATED DATA: ASYMPTOTIC and FINITE SAMPLE RESULTS," Working Papers de Gestão (Management Working Papers) 09, Católica Porto Business School, Universidade Católica Portuguesa.
  83. Bilin Zeng & Xuerong Meggie Wen & Lixing Zhu, 2017. "A link-free sparse group variable selection method for single-index model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(13), pages 2388-2400, October.
  84. Seon-Kyu Kim & Seok-Joong Yun & Jiyeon Kim & Ok-Jun Lee & Suk-Chul Bae & Wun-Jae Kim, 2011. "Identification of Gene Expression Signature Modulated by Nicotinamide in a Mouse Bladder Cancer Model," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-11, October.
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  86. Pedro Duarte Silva, A., 2011. "Two-group classification with high-dimensional correlated data: A factor model approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 2975-2990, November.
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  88. Xu, Ping & Brock, Guy N. & Parrish, Rudolph S., 2009. "Modified linear discriminant analysis approaches for classification of high-dimensional microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1674-1687, March.
  89. Garcia-Magariños Manuel & Antoniadis Anestis & Cao Ricardo & González-Manteiga Wenceslao, 2010. "Lasso Logistic Regression, GSoft and the Cyclic Coordinate Descent Algorithm: Application to Gene Expression Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-30, August.
  90. Chakraborty, Sounak & Guo, Ruixin, 2011. "A Bayesian hybrid Huberized support vector machine and its applications in high-dimensional medical data," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1342-1356, March.
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  113. Un Jung Lee & ShengLi Tzeng & Yu-Chuan Chen & James J Chen, 2017. "Development of Predictive Signatures for Treatment Selection in Precision Medicine," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 2(4), pages 83-88, August.
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