Performance Comparasion of Different Hybrid Approaches for Lung Cancer Recurrence Based on Supervised Learning with Ensemble Techniques
Abstract
Keywords
Full Text:
PDFReferences
Dennis A. Wigle, Igor Jurisica, Niki Radulovich, Melania Pintilie, Janet Rossant, Ni Liu, Chao Lu, James Woodgett, Isolde Seiden, Michael Johnston, Shaf Keshavjee, Gail Darling, Timothy Winton, Bobby-Joe Breitkreutz, Paul Jorgenson, Mike Tyers, Frances A. Shepherd, and Ming Sound Tsao : Molecular Profiling of Non-Small Cell Lung Cancer and Correlation with Disease-free Survival, Cancer Research,62: 3005-3008, 2002.
Travis, W. D., Travis, L. B. and Devesa, S. S.: Lung cancer, International Journal of the American Cancer Society, Volume 75, pg. 191–202. 1995.
Dietterich, T. G.: An Experimental Comparison of Three Methods for constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization, Machine Learning 40: 139–157, 2000.
J.R. Quinlan: Bagging, Boosting and C4.5, Proceedings of the Thirteenth National Conference on Artificial Intelligence, 1996.
Oza, N. C.: Online Bagging and Boosting, IEEE International Conference on Systems, man, Cybernetics, pp. 2340-2345, Vol. 3, 2006.
Sutton, R. S. Barto, A.G.: Reinforcement Learning: An Introduction, IEEE Transaction on Neural Networks, Vol. 9, No. 5, 1998.
Isabelle Guyon, Andre Elisseeff: An Introduction to Variable and Feature Selection, Journal of Machine Learning Research 3, 2003.
Asha Gowda Karegowda, M.A.Jayaram, A.S. Manjunath: Feature Subset Selection Problem using Wrapper Approach in Supervised Learning, International Journal of Computer Applications (0975 – 8887), Volume 1 – No. 7, 2010.
Mazin Aouf, Liwan Liyanage, Stephen Hansen: Critical Review of Data Mining Techniques for Gene Expression Analysis, 4th International Conference on Information and Automation for Sustainability, 2008.
Yvan, Saeys, Inaki Inza, Pedro Larranaga: A review of feature selection techniques in bioinformatics, Bioinformatics, Volume 23, Issue 19, Oxford University Press Oxford, 2007.
Ranjit Abraham, Jay B. Simha and S. Sitharama Iyengar: Effective Discretization and Hybrid feature selection using Naive Bayesian Classifier for Medical data mining, International Journal of Computational Intelligence Research, Vol.5, pp. 116-129, 2009.
Isabelle Guyon, Andre Elisseeff: An Introduction to Variable and Feature Selection, Journal of Machine Learning Research 3, 2003.
Xiangchun Xiong, Yangon Kim, Yuncheol Baek, Dae Wong Rhee, Soo-Hong Kim: Analysis of Breast Cancer Using Data Mining & Statistical Techniques, Proceedings of 6th International Conference on Software Engineering, Artificial Intelligence,2005.
Tao Li, Chengliang Zhang, Mitsunori Ogihara: A Comparative Study of Feature Selection and Multiclass Classification Methods for Tissue Classification Based on Gene Expression, Oxford Journals of Bioinformatics, 2004.
Daniele Soria, Jorathan M. Garibaldi, Elia Biganzoli: A Comparasion of Three Different Methods for Classification of Breast Cancer Data, 7th International Conference on Machine Learning and Application, 2008.
Ying-Wooi Wan, Ebrahim Sabbagh, Rebecca Raese,Yong Qian, Dajie Luo, James Denvir, Val Vallyathan,Vincent Castranova, Nancy Lan Guo: Hybrid Models Identified a 12-Gene Signature for Lung Cancer Prognosis and Chemoresponse Prediction, Journal of PLoS ONE, 2010.
Dietterich, T.G.: Ensemble methods in machine learning. First International Workshop on Multiple Classifier Systems, 2000.
Breiman, L.: Bagging predictors, Machine Learning, 1996.
Hairong Qi: Feature Selection and kNN Fusion in Molecular Classification of Multiple Tumor Types, International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, 2002.
http://www.dtreg.com/svm.htm
R. Markus and P. Carsten: Microarray-based cancer diagnosis with artificial neural networks, BioTechniques Journal, pp. 30–35, 2003.
H. T. Huynh, J. Kim, and Y. Won: DNA microarray classification with compact single hidden layer feed-forward neural networks, Frontiers in the Convergence of Bioscience and Information Technologies (fbit): 193–198, 2007.
Ahmad M. Sarhan: A Novel Gene-Based Cancer Diagnosis with Wavelets and Support Vector Machines, European Journal of Scientific Research, Vol.46 No.4 (2010), pp.488-502,2010.
Michael P.S. Brown et al.: Support Vector Machine Classification of Microarray Gene Expression Data, PNAS, 97 (1): 262-267, 2000.
Seeja K. R., Shweta: Microarray Data Classification Using Support Vector Machine, International Journal of Biometrics and BioInformatics (IJBB), Vol. 5, Issue 1, 2011.
Refbacks
- There are currently no refbacks.