13. Bibliografía

[1]

Donald Bamber. The area above the ordinal dominance graph and the area below the receiver operating characteristic graph. Journal of Mathematical Psychology, 12(4):387–415, 1975.

[2]

Pantelis Bouboulis, Konstantinos Slavakis, and Sergios Theodoridis. Adaptive kernel-based image denoising employing semi-parametric regularization. IEEE Transactions on Image Processing, 19(6):1465–1479, 2010.

[3]

L Breiman, J Friedman, R Olshen, and C Stone. Cart. Classification and Regression Trees, 1984.

[4]

Leo Breiman. Bagging predictors. Machine learning, 24(2):123–140, 1996.

[5]

Leo Breiman. Random forests. Machine learning, 45(1):5–32, 2001.

[6]

Hugh A Chipman, Edward I George, and Robert E McCulloch. Bart: bayesian additive regression trees. The Annals of Applied Statistics, 4(1):266–298, 2010.

[7]

Elizabeth R. DeLong, David M. DeLong, and Daniel L. Clarke-Pearson. Comparing the areas under two or more correlated roc curves. Biometrics, 44(3):837–845, 1988.

[8]

Janez Demšar. Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, 7:1–30, 2006.

[9]

Francis X. Diebold and Roberto S. Mariano. Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3):253–263, 1995.

[10]

Bradley Efron. Bootstrap methods: another look at the jackknife. Annals of Statistics, 7(1):1–26, 1979.

[11]

Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu. A density-based algorithm for discovering clusters in large spatial databases with noise. In Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining (KDD), 226–231. AAAI Press, 1996.

[12]

Jerome H Friedman. Greedy function approximation: a gradient boosting machine. Annals of statistics, pages 1189–1232, 2001.

[13]

Marouane Hachimi, Georges Kaddoum, Ghyslain Gagnon, and Poulmanogo Illy. Multi-stage jamming attacks detection using deep learning combined with kernelized support vector machine in 5g cloud radio access networks. In 2020 international symposium on networks, computers and communications (ISNCC), 1–5. IEEE, 2020.

[14]

James A. Hanley and Barbara J. McNeil. The meaning and use of the area under a roc curve. Radiology, 143(1):29–36, 1982.

[15]

Wassily Hoeffding. A class of statistics with asymptotically normal distribution. Annals of Mathematical Statistics, 19(3):293–325, 1948.

[16]

Arthur E Hoerl and Robert W Kennard. Ridge regression: biased estimation for nonorthogonal problems. Technometrics, 12(1):55–67, 1970.

[17]

Thomas Hofmann, Bernhard Schölkopf, and Alexander J Smola. Kernel methods in machine learning. The annals of statistics, 36(3):1171–1220, 2008.

[18]

Peter J Huber. Robust estimation of a location parameter. In Breakthroughs in statistics, pages 492–518. Springer, 1992.

[19]

Anil K Jain, Robert P. W. Duin, and Jianchang Mao. Statistical pattern recognition: a review. IEEE Transactions on pattern analysis and machine intelligence, 22(1):4–37, 2000.

[20]

Sonia Kahiomba Kiangala and Zenghui Wang. An effective adaptive customization framework for small manufacturing plants using extreme gradient boosting-xgboost and random forest ensemble learning algorithms in an industry 4.0 environment. Machine Learning with Applications, 4:100024, 2021.

[21]

S. Konishi. Introduction to Multivariate Analysis: Linear and Nonlinear Modeling. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis, 2014. ISBN 9781466567283. URL: https://books.google.com.co/books?id=fcuuAwAAQBAJ.

[22]

Konstantinos Koutroumbas and Sergios Theodoridis. Pattern recognition. Academic Press, 2008.

[23]

Hans-Peter Kriegel, Peer Kröger, Jörg Sander, and Arthur Zimek. Density-based clustering. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1(3):231–240, 2011.

[24]

Ludmila I Kuncheva. Combining pattern classifiers: methods and algorithms. John Wiley & Sons, 2014.

[25]

Brian D Ripley. Pattern recognition and neural networks. Cambridge university press, 2007.

[26]

John Shawe-Taylor, Nello Cristianini, and others. Kernel methods for pattern analysis. Cambridge university press, 2004.

[27]

Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore, Alex Kipman, and Andrew Blake. Real-time human pose recognition in parts from single depth images. In CVPR 2011, 1297–1304. Ieee, 2011.

[28]

Konstantinos Slavakis, Pantelis Bouboulis, and Sergios Theodoridis. Online learning in reproducing kernel hilbert spaces. In Academic Press Library in Signal Processing, volume 1, pages 883–987. Elsevier, 2014.

[29]

S. Theodoridis. Machine Learning: A Bayesian and Optimization Perspective. Elsevier Science, 2020. ISBN 9780128188040. URL: https://books.google.com.co/books?id=l-nEDwAAQBAJ.

[30]

David H Wolpert. Stacked generalization. Neural networks, 5(2):241–259, 1992.

[31]

Yuhong Wu, Håkon Tjelmeland, and Mike West. Bayesian cart: prior specification and posterior simulation. Journal of Computational and Graphical Statistics, 16(1):44–66, 2007.

[32]

佐土原健. N. cristianini and j. shawe-taylor: an introduction to support vector machines, cambridge university press (2000). 人工知能, 16(2):337–337, 2001.