Support vector machine ensembles for breast cancer type prediction from mid-FTIR micro-calcification spectra
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Conrad Bessant | Nicholas Stone | Rebecca Baker | Martina Sattlecker | C. Bessant | N. Stone | M. Sattlecker | R. Baker
[1] Claudia Beleites,et al. Assessing and improving the stability of chemometric models in small sample size situations , 2008, Analytical and bioanalytical chemistry.
[2] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[3] Abdel Ghaffmr Mokamed Ahmed,et al. One Against All , 2009 .
[4] Thomas G. Dietterich. Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.
[5] N. Shepherd,et al. New relationships between breast microcalcifications and cancer , 2010, British Journal of Cancer.
[6] Friedhelm Schwenker,et al. Hierarchical support vector machines for multi-class pattern recognition , 2000, KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516).
[7] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[8] Pedro M. Domingos,et al. On the Optimality of the Simple Bayesian Classifier under Zero-One Loss , 1997, Machine Learning.
[9] R. Polikar,et al. Ensemble based systems in decision making , 2006, IEEE Circuits and Systems Magazine.
[10] Dong-Sheng Cao,et al. The boosting: A new idea of building models , 2010 .
[11] Robert Sabourin,et al. “One Against One” or “One Against All”: Which One is Better for Handwriting Recognition with SVMs? , 2006 .
[12] Irccyn,et al. Tenth international workshop on frontiers in handwriting recognition , 2006 .
[13] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.
[14] David H. Wolpert,et al. Stacked generalization , 1992, Neural Networks.
[15] J K Greenson,et al. Reproducibility of the diagnosis of dysplasia in Barrett esophagus: a reaffirmation. , 2001, Human pathology.
[16] Lars Kai Hansen,et al. Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[17] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[18] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[19] Geoffrey E. Hinton,et al. Adaptive Mixtures of Local Experts , 1991, Neural Computation.
[20] D. Titterington,et al. Comparison of Discrimination Techniques Applied to a Complex Data Set of Head Injured Patients , 1981 .
[21] Christoph Krafft,et al. Disease recognition by infrared and Raman spectroscopy , 2009, Journal of biophotonics.
[22] Subhash C. Bagui,et al. Combining Pattern Classifiers: Methods and Algorithms , 2005, Technometrics.
[23] C. Kendall,et al. Vibrational spectroscopy: a clinical tool for cancer diagnostics. , 2009, The Analyst.
[24] Qing-Song Xu,et al. Support vector machines and its applications in chemistry , 2009 .