Feature selection of gene expression data for Cancer classification using double RBF-kernels
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Bin Yu | Xiaoping Liu | Matthias Dehmer | Yusen Zhang | Shenghui Liu | Jiaguo Liu | Chunrui Xu | M. Dehmer | Xiaoping Liu | Yusen Zhang | Bin Yu | Jiaguo Liu | Bin Yu | Chunrui Xu | Xiaoping Liu | Shenghui Liu
[1] Peter Bugata,et al. On some aspects of minimum redundancy maximum relevance feature selection , 2019, Science China Information Sciences.
[2] Huihui Chen,et al. A kernel-based clustering method for gene selection with gene expression data , 2016, J. Biomed. Informatics.
[3] Wei Wu,et al. Transcriptional profiling analysis and functional prediction of long noncoding RNAs in cancer , 2016, Oncotarget.
[4] B. N. Sinha,et al. Studies on Activity of Various Extracts of Albizia amara against Drug induced Gastric Ulcers , 2011 .
[5] Gary D Bader,et al. Visualizing gene-set enrichment results using the Cytoscape plug-in enrichment map. , 2011, Methods in molecular biology.
[6] Raymond J Carroll,et al. Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection , 2010, Journal of the American Statistical Association.
[7] Jin-Kao Hao,et al. Advances in metaheuristics for gene selection and classification of microarray data , 2010, Briefings Bioinform..
[8] Blaise Hanczar,et al. Classification with reject option in gene expression data , 2008, Bioinform..
[9] Pedro Larrañaga,et al. A review of feature selection techniques in bioinformatics , 2007, Bioinform..
[10] Boonserm Kijsirikul,et al. Evolutionary strategies for multi-scale radial basis function kernels in support vector machines , 2005, GECCO '05.
[11] Doheon Lee,et al. Detecting clusters of different geometrical shapes in microarray gene expression data , 2005, Bioinform..
[12] Xin Zhou,et al. LS Bound based gene selection for DNA microarray data , 2005, Bioinform..
[13] Yanqiong Peng,et al. Quantitative tests of interaction between pollinating and non‐pollinating fig wasps on dioecious Ficus hispida , 2005 .
[14] Jason Weston,et al. Gene Selection for Cancer Classification using Support Vector Machines , 2002, Machine Learning.
[15] Chris H. Q. Ding,et al. Minimum redundancy feature selection from microarray gene expression data , 2003, Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003.
[16] Guido Smits,et al. Improved SVM regression using mixtures of kernels , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).
[17] Todd,et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning , 2002, Nature Medicine.
[18] Bernhard Schölkopf,et al. Learning with kernels , 2001 .
[19] M. Xiong,et al. Biomarker Identification by Feature Wrappers , 2022 .
[20] Rithy K. Roth,et al. Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays , 2000, Nature Biotechnology.
[21] Hichem Frigui,et al. Simultaneous clustering and attribute discrimination , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).
[22] Ash A. Alizadeh,et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling , 2000, Nature.
[23] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[24] Theodoros Evgeniou,et al. Learning with kernel machine architectures , 2000 .
[25] Gunnar Rätsch,et al. Input space versus feature space in kernel-based methods , 1999, IEEE Trans. Neural Networks.
[26] U. Alon,et al. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. , 1999, Proceedings of the National Academy of Sciences of the United States of America.
[27] Steven J Skates,et al. Screening for ovarian cancer: a pilot randomised controlled trial , 1999, The Lancet.
[28] Nick Chater,et al. Information gain and decision-theoretic approaches to data selection: Response to Klauer (1999). , 1999 .
[29] Alexander J. Smola,et al. Learning with kernels , 1998 .
[30] Pat Langley,et al. Selection of Relevant Features and Examples in Machine Learning , 1997, Artif. Intell..
[31] J. Claverie,et al. The significance of digital gene expression profiles. , 1997, Genome research.
[32] Vladimir Naumovich Vapni. The Nature of Statistical Learning Theory , 1995 .
[33] Larry A. Rendell,et al. A Practical Approach to Feature Selection , 1992, ML.