Bibliografía¶
Bibliografía¶
- AHH93
Kiyoshi Asai, Satoru Hayamizu, and Ken'ichi Handa. Prediction of protein secondary structure by the hidden markov model. Computer Applications in the Biosciences, 9:141–146, 04 1993. doi:10.1093/bioinformatics/9.2.141.
- BA19
J Barrios Arce. La matriz de confusión y sus métricas. Health Big Data https://www. juanbarrios. com/la-matriz-de-confusion-y-sus-metricas, 2019.
- BLarranaga20
Concha Bielza and Pedro Larrañaga. Data-driven computational neuroscience: machine learning and statistical models. Cambridge University Press, 2020.
- BAZR+17
J.S. Bowman, L.A. Amaral-Zettler, J.J. Rich, C.M. Luria, and H.W. Ducklow. Bacterial community segmentation facilitates the prediction of ecosystem function along the coast ofthe western antarctic peninsula. The ISME Journal, 2017.
- CT18
B. Chopard and M. Tomassini. An Introduction to Metaheuristics for Optimization. Springer, 2018.
- Cor09
J. Cortazar. Memorias de Adriano. Edhasa, 2009.
- CORVV18
M. Cottrell, M. Olteanu, F. Rossi, and N. Villa-Vialeneix. Self-organizing maps, theory and applications. Revista de Investigación Operacional, 39(1):1–22, 2018.
- DHM07
P. Diaconis, S. Holmes, and R. Montgomery. Dynamical bias in the coin toss. SIAM Rev., 49(2):211–235, 2007.
- Eig71
M. Eigen. Self organization of matter and the evolution of biological macromolecules. Naturwissenschaften, 58:465–523, 1971.
- FM08
D. Floreano and C. Mattiussi. Bio-Inspired Artificial Intelligence: Theories, Methods and Technologies. MIT, 2008.
- For06
J. Fort. Som's mathematics. Neural Networks, 19(6-7):812–816, 2006.
- GM00
D. Greenhalgh and S. Marshall. Convergence criteria for genetic algorithms. SIAM J. Comput., 30(1):269–282, 2000.
- Hay13
B. Hayes. First links in the markov chain. American Scientist, 2013.
- Hea08
Jeff Heaton. Introduction to neural networks with Java. Heaton Research, Inc., 2008.
- HMFC17
Jeff Heaton, Steven McElwee, James Fraley, and James Cannady. Early stabilizing feature importance for tensorflow deep neural networks. In 2017 International Joint Conference on Neural Networks (IJCNN), 4618–4624. IEEE, 2017.
- Joh12
M. (Ed.) Johnsson. Applications of Self-Organizing Maps. InTech, 2012.
- Jol86
IT1011 Jolliffe. Generalizations and adaptations of principal component analysis. In Principal Component Analysis, pages 223–234. Springer, 1986.
- KXS+15
H Kaiming, Z Xiangyu, R Shaoqing, and others. Deep residual learning for image recognition. resnet model. arXiv preprint arXiv:1512.03385, 2015.
- Koh82a
T. Kohonen. Analysis of a simple self-organizing process. Biol. Cybern., 44:135–140, 1982.
- Koh82b
T. Kohonen. Self-organized formation of topologically correct feature maps. Biol. Cybern., 43:59–69, 1982.
- Koh95
T. Kohonen. Self-Organizing Maps. Volume 30. Springer Series in Information Science, Springer, 1995.
- Koh00
T. Kohonen. Self-Organizing Maps. Springer-Verlag, 3rd edition edition, 2000.
- Kra17
O. Kramer. Genetic Algorithm Essentials. Springer International Publishing, 2017.
- KSH12
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. Imagenet classification with deep convolutional neural networks (alexnet). Advances in Neural Information Processing Systems 25 (NIPS 2012), 2012.
- Kub15
M. Kubat. An Introduction to Machine Learning. Springer, 2015.
- LBD+89
Yann LeCun, Bernhard Boser, John S Denker, Donnie Henderson, Richard E Howard, Wayne Hubbard, and Lawrence D Jackel. Backpropagation applied to handwritten zip code recognition. Neural computation, 1(4):541–551, 1989.
- LBBH98
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11):2278–2324, 1998.
- LRDMLG14
R. Lorenzo-Redondo, S. Delgado, F. Morán, and C. López-Galíndez. Realistic three dimensional fitness landscapes generated by self organizing maps for the analysis of experimental hiv-1 evolution. PLoS ONE, 9(2):e88579, 2014.
- MP43
Warren S McCulloch and Walter Pitts. A logical calculus of the ideas immanent in nervous activity. The bulletin of mathematical biophysics, 5(4):115–133, 1943.
- Meilua03
Marina Meilă. Comparing clusterings by the variation of information. Learning theory and kernel machines. Springer, 2003.
- Meilua07
Marina Meilă. Comparing clusterings—an information based distance. Journal of multivariate analysis, 98(5):873–895, 2007.
- Mit09
M. Mitchell. Complexity A Guided Tour. UOP USA, 2009.
- MM84
F. Morán and F. Montero. An algorithm to study the evolution and selection of auto replicative molecules. Computers and Chemistry, 8:304–307, 1984.
- NM20
J.C. Nuño and F.J. Muñoz. The partial visibility curve of the feigenbaum cascade to chaos. Chaos, Solitons and Fractals, 2020.
- OK99
E. Oja and S. (Eds.) Kaski. Kohonen Maps. Elsevier Science, 1999.
- RSC13
W.B. Rogers, T. Sinno, and J.C. Crocker. Kinetics and non-exponential binding of dna-coated colloids. Soft Matter, 9(28):6412–6417, 2013.
- Ros58
Frank Rosenblatt. The perceptron: a probabilistic model for information storage and organization in the brain. Psychological review, 65(6):386, 1958.
- RHW86
David E Rumelhart, Geoffrey E Hinton, and Ronald J Williams. Learning representations by back-propagating errors. nature, 323(6088):533–536, 1986.
- SEJ+19
Andrew W Senior, Richard Evans, John Jumper, James Kirkpatrick, Laurent Sifre, Tim Green, Chongli Qin, Augustin Žídek, Alexander WR Nelson, Alex Bridgland, and others. Protein structure prediction using multiple deep neural networks in the 13th critical assessment of protein structure prediction (casp13). Proteins: Structure, Function, and Bioinformatics, 87(12):1141–1148, 2019.
- SLJ+14
C Szegedy, W Liu, Y Jia, P Sermanet, S Reed, D Anguelov, D Erhan, V Vanhoucke, and A Rabinovich. Googlenet. In Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. 2014.
- WH60
Bernard Widrow and Marcian E Hoff. Adaptive switching circuits. Technical Report, Stanford Univ Ca Stanford Electronics Labs, 1960.
- WCXX09
Junjie Wu, Jian Chen, Hui Xiong, and Ming Xie. External validation measures for k-means clustering: a data distribution perspective. Expert Systems with Applications, 36(3):6050–6061, 2009.
- You51
M. Yourcenar. Mémoires d'Hadrien. Plon, 1951.
- ZF12
J. Zhang and H. Fang. Using self-organizing maps to visualize, filter and cluster multidimensional bio-omics data. In Magnus Johnsson, editor, Applications of Self-Organizing Maps, chapter 8, pages 161–179. InTech, Croatia, 2012.