References
- R. Quinlan, 'Induction of Decision Trees,'Machine Learning, Vol. 1, No. 1, pp.81-106, 1986
- R. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers,1993
- S.-B. Park, S.-H. Hwang, and B.-T. Zhang,'Classification of Human Papillomavirus (HPV) Risk Type via Text Mining,Genomics & Informatics, Vol. 1, NO. 2pp. 80-86, 2003
- N. Beerenwinkel. B. Schmidt, H. Walter R. Kaiser, T. Lengauer, D. Hoffmann, K Korn, and J. Selbig, 'Diversity and Complexity of HIV-l Drug Resistance: A Bioinformatics Approach to Predicting Phenotype from Genotype,' PNAS, Vol. 99,No. 12, pp. 8271-8276, 2002
- M. Dettling and P. Buehlmann, 'Boosting for Tumor Classification with Gene Expression Data,' Bioinformatics, Vol. 19,No. 9, pp. 1061-1069, 2003
- S. Lin, S. Patel, A. Duncan, and L.Goodwin, 'Using Decision Trees and Support Vector Machines to Classify Genes by Names,' In Proceedings of the European Workshop on Data Mining and Text Mining for Bioinformatics. pp. 35-41, 2003
- T. Mitchell, Machine Learning, McGraw-Hill, 1997
- G. Stormo, T. Schneider, L. Gold, and A.Ehrenfeucht, 'Use of Perceptron Algorithm to Distinguish Translational Initiation Sites in e.coli.' Nucl. Acids Res., Vol. 10,pp. 2997-3011, 1982
- N. Qian and T. Sejnowski, 'Predicting the Secondary Structure of Globular Proteins Using Neural Network Models,' J. Mol.Biol., Vol 202, pp. 865-884, 1988
- H. Nielsen, J. Engelbrecht, S. Brunak,and G. Heijne, 'Identification of Prokaryotic and Eukaryotic Signal Peptides and Prediction of Their Cleavage Site,' Prot. Eng., Vol. 10, pp. 1-6, 1997
- B.-H. Kim, S.-B. Park, and B.-T. Zhang,'PromSearch: A Hybrid Approach to Human Core-Promoter Prediction,' Lecture Notes in Computer Science, Vol. 3177, pp.125-131, 2004
- V. Vapnik, Statistical Learning Theory,Springer, 1998
- C. Burges, 'A Tutorial on Support Vector Machines for Pattern Recognition,' Data Mlning and Knowledge Discovery, Vol. 2,No. 2, pp. 121-167, 1998
- M. Brown, W. Grundy, D. Lin, N. Cris-tianini, C. Sugnet, T. Furey, M. Ares, and D. Haussler, 'Knowledge-based Analysis of Microarray Gene Expression Data by Using Support Vector Machines,' PNAS Vol. 97, pp. 262-267, 2000
- I. Guyon, J Weston, S. Barnhill, and V. Vapnik, 'Gene Selection for Cancer Classi fication Using Support Vector Machines, Machine Learning, Vol. 46, No. 1, pp.389-422, 2002
- A. Zien, G. Raetsch, S. Mika, B. Scholkopf, T. Lengauer, and K. Muller, 'Engineering Support Vector Machine Kernels that Recognize Translation Initiation Sites, Bioinformatics, Vol. 16, No. 9, pp.799-807, 2000
- C. Ding and I. Dubchak, 'Multi-class Protein Fold Recognition Using Support Vector Machines and Neural Networks, Bioinformatics, Vol. 17, pp. 349-358,2001
- J.-G. Joung, S.-J. 0, and B.-T. Zhang,'Prediction of the Risk Types of Human Papillomaviruses by Support Vector Machines,' Lecture Notes in Artificial Intelligence, Vol. 3157, pp. 723-731,2004
- M. Eisen, P. Spellman, P. Brown, D.Botstein, 'Cluster Analysis and Display of Genome-wide Expression Patterns,' PNAS,Vol. 95, pp 14863-14868, 1998
- P. Tamayo, D. Slonim, J. Mesirov, Q. Zhu, S. Kitareewan, E. Dmitrovsky, E. Lander,and T. Golub, 'Interpreting Patterns of Gene Expression with Self-Organizing Maps: Methods and Application to Hematopoietic Differentiation,' PNAS, Vol.96, pp. 2907-2912, 1999
- B.-T. Zhang, J. Yang, and S.-W. Chi'Self-Organizing Latent Lattice Models forTemporal Gene Expression Profiling,Machine Learning, Vol. 52, No. 1/2, pp.67-89, 2003
- R. Sharan and R. Shamlr, 'CLICK: A Clustering Algorithm with Applications to Gene Expression Analysis,' In Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology, pp. 307-316, 2000
- 박성배, 자연언어 학습을 위한 최대 엔트로피 부스팅 모델, 서울대학교 전기컴퓨터공학부 박사학위 논문, 2002
- S.-B. Park, S.-H. Hwang, and B.-T.Zhang, 'Mining the Risk Types of Human Papillomavirus (HPV) by AdaCost,' Lecture Notes in Computer Science, Vol. 2690, pp.403-412, 2003
- A. Kowalczyk and B. Raskutti, Single Class SVM for Yeast Gene Regulation Prediction, KDD Cup 2002 Task 2 Winner
- K.-J. Lee, Y.-S. Hwang, S.-H. Kim, and H.-C. Rim, 'Biomedical Named Entity Recognition Using Two-phase Model Based on SVMs,' Journal of Biomedical Infor-matics, VOl. 37, No. 6, pp. 436-447, 2004
- V. Hatzivassiloglou, P. Duboue, and A. Rzhetsky, 'Disambiguating Proteins, Genes, and .RNA in Text: A Machine Learning Approach,' Bioinformatics, Vol. 17, Suppl. 1, pp. 97-106, 2001
- J.-D. Kim, T. Ohta, Y. Tateisi, and J.Tsujii, 'GENIA corpus: A Semantically Annotated Corpus for Bio-Textmining, Bioinformatics, Vol. 19, Suppl. 1, pp.180-182, 2003
- S.-B. Park and B.-T. Zhang, 'A Boosted Maximum Entropy Model for Learning Text Chunking,' In Proceedings of the 19th International Conference on MachineLearning, pp. 482-489, 2002
- T. Zhang, F. Damerau, and D. Johnson, 'Text Chunking Based on a Generalization of Winnow,' Journal of Machine Learning Research. Vol. 2, pp. 615-637, 2002