PPT-Are we still talking about diversity in classifier ensemble

Author : lindy-dunigan | Published Date : 2016-06-01

Ludmila I Kuncheva School of Computer Science Bangor University UK Publications 580 Citations 4594 CLASSIFIER ENSEMBLE DIVERSITY Search on 10 Sep 2014 MULTIPLE

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Are we still talking about diversity in classifier ensemble: Transcript

Ludmila I Kuncheva School of Computer Science Bangor University UK Publications 580 Citations 4594 CLASSIFIER ENSEMBLE DIVERSITY Search on 10 Sep 2014 MULTIPLE CLASSIFIER SYSTEMS 30. . Thorpex-Tigge. . and use in Applications. Tom Hopson. Outline. Thorpex. -Tigge. data set. Ensemble forecast examples:. a) Southwestern African . flooding. . TIGGE, the THORPEX Interactive Grand Global Ensemble. Dominic . Cockman. , . Jesper. Madsen, . Qiuzhen. Zhu. 1. L. earning . C. lassifier. . S. ystems. History and Motivations. 2. History and Motivations for LCS. Robust . machine learning techniques that can be applied to classification tasks, large-scale data mining problems or robot control and cognitive system applications, among . Ensemble Clustering. unlabeled . data. ……. F. inal . partition. clustering algorithm 1. combine. clustering algorithm . N. ……. clustering algorithm 2. Combine multiple partitions of . given. data . fundamentals. Tom Hamill. NOAA ESRL, Physical Sciences Division. tom.hamill@noaa.gov. NOAA Earth System. Research Laboratory. “Ensemble weather prediction”. possibly. different. models. or models. Slides to include. MODIS land use slide from Tanya with . Zo. Show time-lagged ensemble of updraft . helicity. – source . for idea. Kalman. Filters. Yun Liu. Dept. of Atmospheric and Oceanic . Science, University of Maryland . Atmospheric and oceanic . s. ciences and Center for Climatic . R. esearch, UW-Madison. Collaborators: X. . and post-processing . team reports to NGGPS. Tom Hamill. ESRL, Physical Sciences Division. tom.hamill@noaa.gov. (303) 497-3060. 1. Proposed team . members. Ensemble system development. Post-processing. Geo-Resources and Environment. Lab, Bordeaux INP (. Bordeaux Institute of Technology. ), France. Supervisor. : . Samia . BOUKIR. CLASSIFICATION OF SATELLITE IMAGES USING MARGIN-BASED ENSEMBLE METHODS. APPLICATION TO LAND COVER MAPPING OF NATURAL SITES . Ensemble Methods. Bamshad Mobasher. DePaul University. Ensemble methods. Use a combination of models to increase accuracy. Combine a series of k learned models, . M. 1, . M. 2, …, . Mk. , with the aim of creating an improved model . Dongsheng. Luo, Chen Gong, . Renjun. Hu. , Liang . Duan. Shuai. Ma, . Niannian. Wu, . Xuelian. Lin. TeamBUAA. Problem & Challenges. Problem: . rank nodes in a heterogeneous graph based on query-independent node importance . Bright, . Colle. , . DiMego. , Hacker, Whitaker. 22 Aug. 2012. DTC SAB ensemble task. 1. Primary recommendation. Continue to pursue long-term goal of pivotal and more tangible role in research-to-operations (R2O) transitions. . Ludmila. . Kuncheva. School of Computer Science. Bangor University. mas00a@bangor.ac.uk. . Part 2. 1. Combiner. Features. Classifier 2. Classifier 1. Classifier L. …. Data set. A . . Combination level. Kalman. filter. Part I: The Big Idea. Alison Fowler. Intensive course on advanced data-assimilation methods. 3-4. th. March 2016, University of Reading. Recap of problem we wish to solve. Given . prior knowledge . Modeling and Development Division. CPTEC/INPE. Middle-Range Ensemble Forecast at CPTEC/INPE - Current Activities. 2. Local Ensemble Transformed . Kalman. Filter. OUTLINE. 3. New method to obtain perturbed initial conditions .

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