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Artykuły w czasopismach na temat "Bayesian classification"
Yazdi, Hadi Sadoghi, Mehri Sadoghi Yazdi i Abedin Vahedian. "Fuzzy Bayesian Classification of LR Fuzzy Numbers". International Journal of Engineering and Technology 1, nr 5 (2009): 415–23. http://dx.doi.org/10.7763/ijet.2009.v1.78.
Pełny tekst źródłaWang, ShuangCheng, GuangLin Xu i RuiJie Du. "Restricted Bayesian classification networks". Science China Information Sciences 56, nr 7 (9.01.2013): 1–15. http://dx.doi.org/10.1007/s11432-012-4729-x.
Pełny tekst źródłaBerrett, Candace, i Catherine A. Calder. "Bayesian spatial binary classification". Spatial Statistics 16 (maj 2016): 72–102. http://dx.doi.org/10.1016/j.spasta.2016.01.004.
Pełny tekst źródłaDojer, Norbert, Paweł Bednarz, Agnieszka Podsiadło i Bartek Wilczyński. "BNFinder2: Faster Bayesian network learning and Bayesian classification". Bioinformatics 29, nr 16 (1.07.2013): 2068–70. http://dx.doi.org/10.1093/bioinformatics/btt323.
Pełny tekst źródłaReguzzoni, M., F. Sansò, G. Venuti i P. A. Brivio. "Bayesian classification by data augmentation". International Journal of Remote Sensing 24, nr 20 (styczeń 2003): 3961–81. http://dx.doi.org/10.1080/0143116031000103817.
Pełny tekst źródłaWang, Xiaohui, Shubhankar Ray i Bani K. Mallick. "Bayesian Curve Classification Using Wavelets". Journal of the American Statistical Association 102, nr 479 (wrzesień 2007): 962–73. http://dx.doi.org/10.1198/016214507000000455.
Pełny tekst źródłaWilliams, C. K. I., i D. Barber. "Bayesian classification with Gaussian processes". IEEE Transactions on Pattern Analysis and Machine Intelligence 20, nr 12 (1998): 1342–51. http://dx.doi.org/10.1109/34.735807.
Pełny tekst źródłaDellaportas, Petros. "Bayesian classification of Neolithic tools". Journal of the Royal Statistical Society: Series C (Applied Statistics) 47, nr 2 (28.06.2008): 279–97. http://dx.doi.org/10.1111/1467-9876.00112.
Pełny tekst źródłaMiguel Hernández-Lobato, Jose, Daniel Hernández-Lobato i Alberto Suárez. "Network-based sparse Bayesian classification". Pattern Recognition 44, nr 4 (kwiecień 2011): 886–900. http://dx.doi.org/10.1016/j.patcog.2010.10.016.
Pełny tekst źródłaHunter, L., i D. J. States. "Bayesian classification of protein structure". IEEE Expert 7, nr 4 (sierpień 1992): 67–75. http://dx.doi.org/10.1109/64.153466.
Pełny tekst źródłaRozprawy doktorskie na temat "Bayesian classification"
Nappa, Dario. "Bayesian classification using Bayesian additive and regression trees". Ann Arbor, Mich. : ProQuest, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3336814.
Pełny tekst źródłaTitle from PDF title page (viewed Mar. 16, 2009). Source: Dissertation Abstracts International, Volume: 69-12, Section: B, page: . Adviser: Xinlei Wang. Includes bibliographical references.
Haywood, Andries Stefan. "Bayesian object classification in nanoimages". Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/63790.
Pełny tekst źródłaMini Dissertaion (MSc)--University of Pretoria, 2017.
NRF (under CSUR grant 90315)
CSIR
Statistics
MSc
Unrestricted
Anderson, Michael P. "Bayesian classification of DNA barcodes". Diss., Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/2247.
Pełny tekst źródłaGibbs, M. N. "Bayesian Gaussian processes for regression and classification". Thesis, University of Cambridge, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.599379.
Pełny tekst źródłaDe, Lance Holmes Christopher Charles. "Bayesian method for nonlinear classification and regression". Thesis, Imperial College London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.394926.
Pełny tekst źródłaChan, Kwokleung. "Bayesian learning in classification and density estimation /". Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC IP addresses, 2002. http://wwwlib.umi.com/cr/ucsd/fullcit?p3061619.
Pełny tekst źródłaWang, Xiaohui. "Bayesian classification and survival analysis with curve predictors". [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1205.
Pełny tekst źródłaLoza, Reyes Elisa. "Classification of phylogenetic data via Bayesian mixture modelling". Thesis, University of Bath, 2010. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.519916.
Pełny tekst źródłaCooley, Craig Allen. "Bayesian and nonparametric models in the classification problem /". The Ohio State University, 1996. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487935573773741.
Pełny tekst źródłaSchmidt, Aurora Clare 1981. "Dynamic Bayesian networks for the classification of spinning discs". Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/16686.
Pełny tekst źródłaIncludes bibliographical references (p. 87-89).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
This thesis considers issues for the application of particle filters to a class of nonlinear filtering and classification problems. Specifically, we study a prototype system of spinning discs. The system combines linear dynamics describing rotation with a nonlinear observation model determined by the disc pattern, which is parameterized by angle. A consequence of the nonlinear observation model is that the posterior state distribution of angle and spin-rate is multi-modal. This detail motivates the use of particle filtering. Practical issues that we consider when using particle filters are sample depletion and sample degeneracy, both of which lead to poor representations of the state distributions. Variance based resampling and regularization are common methods to mitigate sampling issues in particle filtering. We investigate these methods empirically for our prototype problem. Specific parameters of interest relating to these methods are the number of particles used to approximate the posterior distribution, quantitative methods for deciding when to resample, choice of regularization variance, the impact of measurement noise on all of these, and performance over time. A common issue, leading to inaccurate sample-based representations, is the case of relatively low measurement noise combined with an insufficient number of particles. Our empirical results show that for relatively smooth patterns (e.g. linear, cosine) particle filters were less susceptible to sampling issues than for patterns with higher frequency content. The goal of our experiments is to quantify the nature of these differences.
by Aurora Clare Schmidt.
M.Eng.
Książki na temat "Bayesian classification"
T, Denison David G., red. Bayesian methods for nonlinear classification and regression. Chichester, England: Wiley, 2002.
Znajdź pełny tekst źródłaPAC-Bayesian supervised classification: The thermodynamics of statistical learning. Beachwood, Ohio: Institute of Mathematical Statistics, 2007.
Znajdź pełny tekst źródłaFrey, Brendan J. Bayesian networks for pattern classification, data compression, and channel coding. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1997.
Znajdź pełny tekst źródłaNeal, Radford M. Monte Carlo implementation of Gaussian process models for Bayesian regression and classification. Toronto: University of Toronto, 1997.
Znajdź pełny tekst źródłaPress, S. James. Bayesian statistics: Principles, models, and applications. New York: Wiley, 1989.
Znajdź pełny tekst źródłaWang, Jun. A Bayesian classifier based on a deterministic annealing neural network for aircraft fault classification. Wright-Patterson AFB, OH: Human Resources Directorate, Logistics Research Division, U.S. Air Force Armstrong Laboratory, 1997.
Znajdź pełny tekst źródłaAbkar, Ali Akbar. Likelihood-based segmentation and classification of remotely sensed images: A Bayesian optimization approach for combining RS and GIS. Enschede, The Netherlands: International Institute for Aerospace Survey and Earth Sciences, 1999.
Znajdź pełny tekst źródłaJohn, Stutz, Cheeseman Peter i Ames Research Center. Artificial Intelligence Research Branch., red. Bayesian classification theory. Moffett Field, CA: NASA Ames Research Center, Artificial Intelligence Research Branch, 1991.
Znajdź pełny tekst źródłaDalton, Lori A., i Edward R. Dougherty. Optimal Bayesian Classification. SPIE, 2020.
Znajdź pełny tekst źródłaDalton, Lori A., i Edward R. Dougherty. Optimal Bayesian Classification. SPIE, 2020. http://dx.doi.org/10.1117/3.2540669.
Pełny tekst źródłaCzęści książek na temat "Bayesian classification"
Zhang, Dengsheng. "Bayesian Classification". W Texts in Computer Science, 161–78. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17989-2_7.
Pełny tekst źródłaHsu, Wynne. "Bayesian Classification". W Encyclopedia of Database Systems, 1–5. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_556-2.
Pełny tekst źródłaHsu, Wynne. "Bayesian Classification". W Encyclopedia of Database Systems, 210–14. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_556.
Pełny tekst źródłaZhang, Dengsheng. "Bayesian Classification". W Texts in Computer Science, 183–200. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69251-3_7.
Pełny tekst źródłaHsu, Wynne. "Bayesian Classification". W Encyclopedia of Database Systems, 263–67. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_556.
Pełny tekst źródłaAlmond, Russell G., i Juan-Diego Zapata-Rivera. "Bayesian Networks". W Handbook of Diagnostic Classification Models, 81–106. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05584-4_4.
Pełny tekst źródłaSebastiani, Paola, i Marco Ramoni. "Robust Bayesian classification". W COMPSTAT, 445–50. Heidelberg: Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-642-57678-2_61.
Pełny tekst źródłaWinkler, Gerhard. "Bayesian Texture Classification". W Image Analysis, Random Fields and Markov Chain Monte Carlo Methods, 243–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55760-6_17.
Pełny tekst źródłaKoch, Karl-Rudolf. "Classification". W Bayesian Inference with Geodetic Applications, 135–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/bfb0048714.
Pełny tekst źródłaBernardo, José M. "Bayesian Linear Probabilistic Classification". W Statistical Decision Theory and Related Topics IV, 151–62. New York, NY: Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4613-8768-8_19.
Pełny tekst źródłaStreszczenia konferencji na temat "Bayesian classification"
Rodríguez-Teja, Federico, Carlos Martinez-Cagnazzo i Eduardo Grampín Castro. "Bayesian classification". W the 6th International Wireless Communications and Mobile Computing Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1815396.1815572.
Pełny tekst źródłaChakrabarty, Dalia, i Coryn A. L. Bailer-Jones. "A Novel Bayesian Mass Determination Algorithm". W CLASSIFICATION AND DISCOVERY IN LARGE ASTRONOMICAL SURVEYS: Proceedings of the International Conference: “Classification and Discovery in Large Astronomical Surveys”. AIP, 2008. http://dx.doi.org/10.1063/1.3059070.
Pełny tekst źródłaRichards, Gordon T., i Coryn A. L. Bailer-Jones. "Bayesian Quasar Selection and the Quasar Luminosity Function". W CLASSIFICATION AND DISCOVERY IN LARGE ASTRONOMICAL SURVEYS: Proceedings of the International Conference: “Classification and Discovery in Large Astronomical Surveys”. AIP, 2008. http://dx.doi.org/10.1063/1.3059053.
Pełny tekst źródłaPiro, Paolo, Richard Nock, Frank Nielsen i Michel Barlaud. "Boosting Bayesian MAP Classification". W 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.167.
Pełny tekst źródłaKeren, Carmit, Miriam Zacksenhouse i Yakov Ben-Haim. "Info Gap Bayesian Classification". W ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59188.
Pełny tekst źródła"LEUKOCYTES CLASSIFICATION USING BAYESIAN NETWORKS". W 3rd International Conference on Agents and Artificial Intelligence. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003197706810684.
Pełny tekst źródłaSonneland, L., P. Tennebo, T. Gehrmann i O. Yrke. "3D Model-based Bayesian classification". W 56th EAEG Meeting. European Association of Geoscientists & Engineers, 1994. http://dx.doi.org/10.3997/2214-4609.201410086.
Pełny tekst źródłaMukhopadhyay, Subhadeep, Faming Liang, Paul M. Goggans i Chun-Yong Chan. "Bayesian Analysis of High Dimensional Classification". W BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: The 29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2009. http://dx.doi.org/10.1063/1.3275621.
Pełny tekst źródłaJi Won Yoon, Stephen J. Roberts, Matt Dyson i John Q. Gan. "Sequential Bayesian estimation for adaptive classification". W 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2008). IEEE, 2008. http://dx.doi.org/10.1109/mfi.2008.4648010.
Pełny tekst źródłaBulo, Samuel Rota, i Peter Kontschieder. "Online Learning with Bayesian Classification Trees". W 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016. http://dx.doi.org/10.1109/cvpr.2016.432.
Pełny tekst źródłaRaporty organizacyjne na temat "Bayesian classification"
Zhan, Zhijun, LiWu Chang i Stan Matwin. Privacy-Preserving Naive Bayesian Classification. Fort Belvoir, VA: Defense Technical Information Center, styczeń 2004. http://dx.doi.org/10.21236/ada464290.
Pełny tekst źródłaBarker, Kash, Theodore B. Trafalis i Cameron A. MacKenzie. Bayesian Kernel Methods for Non-Gaussian Distributions: Binary and Multi-class Classification Problems. Fort Belvoir, VA: Defense Technical Information Center, maj 2013. http://dx.doi.org/10.21236/ada595533.
Pełny tekst źródłaYeung, Ka Y., Roger E. Bumgarner i Adrian E. Raftery. Bayesian Model Averaging: Development of an Improved Multi-Class, Gene Selection and Classification Tool for Microarray Data. Fort Belvoir, VA: Defense Technical Information Center, październik 2004. http://dx.doi.org/10.21236/ada454826.
Pełny tekst źródłaTian, Cong, Jianlong Shu, Wenhui Shao, Zhengxin Zhou, Huayang Guo i Jingang Wang. The efficacy and safety of IL Inhibitors, TNF-α Inhibitors, and JAK Inhibitor on ankylosing spondylitis: A Bayesian network meta-analysis of a “randomized, double-blind, placebo-controlled” trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, wrzesień 2022. http://dx.doi.org/10.37766/inplasy2022.9.0117.
Pełny tekst źródłaKingston, A. W., A. Mort, C. Deblonde i O H Ardakani. Hydrogen sulfide (H2S) distribution in the Triassic Montney Formation of the Western Canadian Sedimentary Basin. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329797.
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