PHÂN LOẠI DỮ LIỆU GIEN VỚI GIẢI THUẬT MÁY HỌC ARCX4-RODT
Abstract
Tóm tắt
Article Details
Tài liệu tham khảo
L. Breiman, J.H. Friedman, R.A. Olshen and C. Stone. Classification and Regression Trees. Wadsworth International, 1984.
L. Breiman. Bagging predictors. Machine Learning 24(2):123–140, 1996.
L. Breiman. Arcing classifiers. The annals of statistics, 26(3): 801–849, 1998.
L. Breiman. Random forests. Machine Learning 45(1):5–32, 2001.
W. Buntine. Learning classification trees. Statistics and Computing 2, 1992, pp. 63–73.
C.C. Chang and C.J. Lin. Libsvm – a library for support vector machines. 2001. http://www.csie.ntu.edu.tw/cjlin/libsvm.
T.N. Do, S. Lallich, N.K. Pham and P. Lenca. Classifying very-high-dimensional data with random forests of oblique decision trees. in Advances in Knowledge Discovery and Management Vol. 292, Springer-Verlag, 2009, pp. 39-55.
R.A. Fisher. The Use of Multiple Measurements in Taxonomic Problems. in Annals of Eugenics, No 7, 1936, pp. 179-188.
Y. Freund and R. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. Computational Learning Theory, 1995, pp. 23–37.
J. Friedman, T. Hastie and R. Tibshirani. Response to Mease and Wyner, Evidence Contrary to the Statistical View of Boosting. Journal Machine Learning Research Vol. 9, 2008, pp. 175-180.
A.J. Grove and D. Schuurmans. Boosting in the limit: Maximizing the margin of learned ensembles. In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), 1998, pp. 692–699.
L. Jinyan and L. Huiqing. Kent ridge bio-medical dataset repository. 2002, http://datam.i2r.a-star.edu.sg/datasets/krbd/.
S. Murthy, S. Kasif, S. Salzberg and R. Beigel. Oc1: Randomized induction of oblique decision trees. In Proceedings of the Eleventh National Conference on Artificial Intelligence, 1993, pp. 322–327.
J.R. Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, 1993.
C.V. van Rijsbergen. Information Retrieval. Butterworth, 1979.
V. Vapnik. The Nature of Statistical Learning Theory. Springer-Verlag, 1995.
D. Wolpert. Stacked generalization. Neural Networks 5, 1992, pp. 241–259.
Q. Yang and X. Wu. 10 Challenging Problems in Data Mining Research. Journal of Information Technology & Decision Making 5(4):597-604, 2006.