Academic literature on the topic 'Best Subset Selection'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Best Subset Selection.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Best Subset Selection"
Groz, Benoît, and Silviu Maniu. "Hypervolume Subset Selection with Small Subsets." Evolutionary Computation 27, no. 4 (December 2019): 611–37. http://dx.doi.org/10.1162/evco_a_00235.
Full textTamura, Ryuta, Ken Kobayashi, Yuichi Takano, Ryuhei Miyashiro, Kazuhide Nakata, and Tomomi Matsui. "BEST SUBSET SELECTION FOR ELIMINATING MULTICOLLINEARITY." Journal of the Operations Research Society of Japan 60, no. 3 (2017): 321–36. http://dx.doi.org/10.15807/jorsj.60.321.
Full textAlrefaei, Mahmoud H., and Mohammad Almomani. "Subset selection of best simulated systems." Journal of the Franklin Institute 344, no. 5 (August 2007): 495–506. http://dx.doi.org/10.1016/j.jfranklin.2006.02.020.
Full textBofinger, Evc, and Kerrie Mangersen. "Subset selection of the t best populations." Communications in Statistics - Theory and Methods 15, no. 10 (January 1986): 3145–61. http://dx.doi.org/10.1080/03610928608829299.
Full textTakano, Yuichi, and Ryuhei Miyashiro. "Best subset selection via cross-validation criterion." TOP 28, no. 2 (February 14, 2020): 475–88. http://dx.doi.org/10.1007/s11750-020-00538-1.
Full textGupta, Shanti S., and Hwa-Ming Yang. "subset selection procedures for the best population." Journal of Statistical Planning and Inference 12 (January 1985): 213–33. http://dx.doi.org/10.1016/0378-3758(85)90071-0.
Full textLaan, Paul Van Der, and Paul van der Laan. "Subset Selection of an Almost Best Treatment." Biometrical Journal 34, no. 6 (1992): 647–56. http://dx.doi.org/10.1002/bimj.4710340602.
Full textZhang, Zhongheng. "Variable selection with stepwise and best subset approaches." Annals of Translational Medicine 4, no. 7 (April 2016): 136. http://dx.doi.org/10.21037/atm.2016.03.35.
Full textZhu, Junxian, Canhong Wen, Jin Zhu, Heping Zhang, and Xueqin Wang. "A polynomial algorithm for best-subset selection problem." Proceedings of the National Academy of Sciences 117, no. 52 (December 16, 2020): 33117–23. http://dx.doi.org/10.1073/pnas.2014241117.
Full textBertsimas, Dimitris, Angela King, and Rahul Mazumder. "Best subset selection via a modern optimization lens." Annals of Statistics 44, no. 2 (April 2016): 813–52. http://dx.doi.org/10.1214/15-aos1388.
Full textDissertations / Theses on the topic "Best Subset Selection"
Zhang, Tao. "Discrepancy-based algorithms for best-subset model selection." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/4800.
Full textCarter, Knute Derek. "Best-subset model selection based on multitudinal assessments of likelihood improvements." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/5726.
Full textHaeggström, Andreas, and Jennie Sund. "Prognosmodell för svenska läns bruttoregionalprodukt (BRP) : En komparativ analys av bayesian model averaging, best subset selection och en longitudinell modell." Thesis, Umeå universitet, Statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-105339.
Full textLiu, Feng-Chi, and 劉峰旗. "Best Subset Selection of AR-GARCH Models." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/45538737888749003214.
Full textMcLean, Kevin. "Obtaining the Best Model Predictions and Parameter Estimates Using Limited Data." Thesis, 2011. http://hdl.handle.net/1974/6757.
Full textThesis (Master, Chemical Engineering) -- Queen's University, 2011-09-27 10:52:31.588
Chung, Yu-Wei, and 莊昱偉. "Monte Carlo Sampling of Sequential Likelihood Procedure for Selecting a Subset of Size s which are contained in the Best t (t>=s) populations." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/09111651118401105662.
Full text淡江大學
數學系
83
In many of the experimental situations, one is faced with the problems, e.g. drug efficiency, crop yields, etc, of selecting the better ones from a given collection. Bechhofer (1954) developed a procedure based on predetermined number of observations from normal population's with unknown mean and known variance. Mahamunulu(1967) considered a fixed-sample procedure of selecting a subset of size s which contains at least c of the t best populations.(max(1,s+t+1-k)=
Books on the topic "Best Subset Selection"
Hurtado de Mendoza, Diego, 1503-1575, Kelly, Jerry, 1955- book designer, Morillon Antoine d. 1522-1556, and Association internationale de bibliophilie, eds. Index of best authors: By subject classification compiled in 1547 by Antoine Morillon : for Antoine Perrenot de Granvelle including a selection of Greek manuscripts in the library of Diego Hurtado de Mendoza : (Besançon, Bibliothèque Municipale, MS Granvelle 90, ff. 11- 18v). [Place of publication not identified]: Prepared for the visit to Besançon by the Association internationale de bibliophilie, 2014.
Find full textHankin, David, Michael S. Mohr, and Kenneth B. Newman. Sampling Theory. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198815792.001.0001.
Full textChow, Jade, John Patterson, Kathy Boursicot, and David Sales, eds. Oxford Assess and Progress: Medical Sciences. Oxford University Press, 2012. http://dx.doi.org/10.1093/oso/9780199605071.001.0001.
Full textMinelli, Alessandro. Evolvability and Its Evolvability. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199377176.003.0007.
Full textRutherford, Donald, ed. Oxford Studies in Early Modern Philosophy, Volume X. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192897442.001.0001.
Full textManson, S. S., and G. R. Halford. Fatigue and Durability of Structural Materials. ASM International, 2006. http://dx.doi.org/10.31399/asm.tb.fdsm.9781627083447.
Full textRutherford, Donald, ed. Oxford Studies in Early Modern Philosophy, Volume IX. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198852452.001.0001.
Full textLetters and pape[rs] on agriculture: Extracted from the correspondence of a society instituted at Halifax, for promoting agriculture in the province of Nova-Scotia ; to which is added a selection of papers on various branches of husbandry, from some of the best publications on the subject in Europe and America. Halifax: Printed by J. Howe, 1990.
Find full textBook chapters on the topic "Best Subset Selection"
Tuv, Eugene, Alexander Borisov, and Kari Torkkola. "Best Subset Feature Selection for Massive Mixed-Type Problems." In Intelligent Data Engineering and Automated Learning – IDEAL 2006, 1048–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11875581_125.
Full textGonzalez, P. L., R. Cléroux, and B. Rioux. "Selecting the Best Subset of Variables in Principal Component Analysis." In Compstat, 115–20. Heidelberg: Physica-Verlag HD, 1990. http://dx.doi.org/10.1007/978-3-642-50096-1_18.
Full textChakraborty, Basabi. "Particle Swarm Optimization Algorithm and its Hybrid Variants for Feature Subset Selection." In Handbook of Research on Computational Intelligence for Engineering, Science, and Business, 449–66. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2518-1.ch017.
Full textNechval, Nicholas A., Konstantin N. Nechval, Maris Purgailis, and Uldis Rozevskis. "Selection of the Best Subset of Variables in Regression and Time Series Models." In Cybernetics and Systems Theory in Management, 303–20. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-668-1.ch016.
Full textTiwari, Arvind Kumar. "Feature Selection Algorithms for Classification and Clustering." In Cognitive Analytics, 422–42. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2460-2.ch022.
Full textTiwari, Arvind Kumar. "Feature Selection Algorithms for Classification and Clustering." In Ubiquitous Machine Learning and Its Applications, 143–67. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2545-5.ch007.
Full textDhamodharavadhani S. and Rathipriya R. "Variable Selection Method for Regression Models Using Computational Intelligence Techniques." In Handbook of Research on Machine and Deep Learning Applications for Cyber Security, 416–36. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9611-0.ch019.
Full textDhamodharavadhani S. and Rathipriya R. "Variable Selection Method for Regression Models Using Computational Intelligence Techniques." In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, 742–61. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8048-6.ch037.
Full textBidi, Noria, and Zakaria Elberrichi. "Best Features Selection for Biomedical Data Classification Using Seven Spot Ladybird Optimization Algorithm." In Cognitive Analytics, 407–21. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2460-2.ch021.
Full textAlaoui, Abdiya, and Zakaria Elberrichi. "Enhanced Ant Colony Algorithm for Best Features Selection for a Decision Tree Classification of Medical Data." In Advances in Library and Information Science, 278–93. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1021-6.ch015.
Full textConference papers on the topic "Best Subset Selection"
Wang, Yu, Louis Luangkesorn, and Larry J. Shuman. "Best-subset selection procedure." In 2011 Winter Simulation Conference - (WSC 2011). IEEE, 2011. http://dx.doi.org/10.1109/wsc.2011.6148118.
Full textGieseke, Fabian, Kai Lars Polsterer, Ashish Mahabal, Christian Igel, and Tom Heskes. "Massively-parallel best subset selection for ordinary least-squares regression." In 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2017. http://dx.doi.org/10.1109/ssci.2017.8285225.
Full textZhang, Ping, Ju Jiang, Xueshan Han, and Zhuoxun Lin. "M-best subset selection from n alternatives based on genetic algorithm." In 2011 24th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2011. http://dx.doi.org/10.1109/ccece.2011.6030526.
Full textJoshi, Alok A., Peter H. Meckl, Galen B. King, and Kristofer Jennings. "Information-Theoretic Sensor Subset Selection: Application to Signal-Based Fault Isolation in Diesel Engines." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-15903.
Full textQian, Chao, Yang Yu, and Ke Tang. "Approximation Guarantees of Stochastic Greedy Algorithms for Subset Selection." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/205.
Full textBigler, Tamara, and Oliver Strub. "A Local-branching Heuristic for the Best Subset Selection Problem in Linear Regression." In 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2018. http://dx.doi.org/10.1109/ieem.2018.8607366.
Full textBian, Chao, Chao Qian, Frank Neumann, and Yang Yu. "Fast Pareto Optimization for Subset Selection with Dynamic Cost Constraints." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/302.
Full textCross, Valerie, and Michael Zmuda. "Ensemble Creation using Fuzzy Similarity Measures and Feature Subset Evaluators." In 2nd International Conference on Machine Learning Techniques and NLP (MLNLP 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111407.
Full textGu, Lei. "A Comparison of Polynomial Based Regression Models in Vehicle Safety Analysis." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/dac-21063.
Full textDereziński, Michał, Rajiv Khanna, and Michael W. Mahoney. "Improved Guarantees and a Multiple-descent Curve for Column Subset Selection and the Nystrom Method (Extended Abstract)." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/647.
Full textReports on the topic "Best Subset Selection"
Seginer, Ido, James Jones, Per-Olof Gutman, and Eduardo Vallejos. Optimal Environmental Control for Indeterminate Greenhouse Crops. United States Department of Agriculture, August 1997. http://dx.doi.org/10.32747/1997.7613034.bard.
Full text