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Need statistical tests for comparing expected costs of different classifiers and ... Comparing Misclassification Costs: BDELTACOST ...
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Ensembles for Cost-Sensitive Learning Thomas G. Dietterich Department of Computer Science Oregon State University Corvallis, Oregon 97331 http://www.cs.orst.edu/~tgd
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Margaret Burnett. Simone Stumpf. Tom Dietterich. Jon Herlocker. Erin Fitzhenry. Lida Li ... S., Rajaram V., Li L., Burnett M., Dietterich T., Sullivan E. ...
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Charles Rosenberg. Thesis Oral. May 10, 2004. Thesis Committee. Martial Hebert, co-chair ... Dietterich, Lathrop, Lozano-Perez, AI 97. Maron, Lozano-Perez, NIPS 1998. ...
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Robust Fisher Discriminant Analysis Article presented at NIPS 2005 By Seung-Jean Kim, Alessandro Magnani, Stephen P. Boyd Presenter: Erick Delage
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Sketched Derivation of error bound using VC-dimension (1) Bound our usual PAC expression by the probability that an algorithm has 0 error on the training examples S ...
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Paul Cohen, Empirical Methods in Artificial Intelligence, MIT Press, 1995. ... Required too much expert time. Limited set of experts (all from Stanford Hospital) ...
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Title: PowerPoint Presentation Last modified by: HX Created Date: 1/1/1601 12:00:00 AM Document presentation format: Other titles
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Bowdoin Computational Sustainability: Computational Methods for a Sustainable Environment, Economy, and Society Carla P. Gomes (Lead PI Cornell University)
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Department of Computer Science and Engineering. Arizona State University ... In majority of experiments, 0 is in the confidence interval, meaning the ...
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In the training data, label value 2 is the only label value observed after label ... MEMM fails to discriminate between the two branches. CRF solves label bias problem ...
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(Selective Ensemble) http://cs.nju.edu.cn/people/zhouzh/ Email: zhouzh@nju.edu.cn
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Evaluation criteria should be measurable and meaningful ... Measurable Criteria. Ideally, your evaluation criteria should be: Easy to measure ...
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'A divide-and-conquer approach to learning from prior knowledge' ... vegetation (LAI tuple: tree, grass, and shrub) and biome classification (Runoff? ...
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An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
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Text and speech processing, including topic segmentation, part-of-speech ... Prelude the use of prior, which is very valuable (e.g. in information extraction) ...
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Robert L. Peters, Getting What You Came For: The Smart Student's Guide to ... Words from the Wise. September1999. October 1999. 2/19 and 2/26/09. 31 ...
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... typically trained to maximize the joint likelihood of train examples ... Given training set X with label sequence Y: Train a model ? that maximizes P(Y|X, ?) ...
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... that work in a derived feature space and maximize margin. Perceptrons ... the derived feature , XOR becomes linearly ... Let. Where: ...(we can do XOR! ...
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Random split selection does better than bagging; introduction of random noise ... In each iteration, 10% of the data was split off as a test set. ...
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... phone rings TaskTracer uses caller id to identify the caller, locates tasks ... task, and prominently lists past emails and phone calls to and from that caller. ...
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Title: PowerPoint Presentation Author: Learning Agents Laboratory Last modified by: Gheorghe Tecuci Created Date: 10/16/2000 12:50:33 AM Document presentation format
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Two tasks are MTL/BP related if there is correlation (positive or negative) ... stock market. economic forecasting. weather prediction. spatial series. many more ...
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Bruce R. Maxim. Jan Hajic. Srinath Srinivasa. Simeon Ntafos. Paolo ... Lee McCluskey. David J. Kriegman. Kathleen McKeown. Michael J. Ciaraldi. David Finkel ...
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Regression: to train an autonomous car to predict what angle to turn the ... Posted on the website (calendar) Three volunteers: Lewis, Natalia, and T.K. ...
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stock market. economic forecasting. weather prediction. spatial series. many more ... Pratt, Mostow [1991-94]: serial transfer in bp nets ...
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Title: PowerPoint Presentation Author: xjliao Last modified by: xjliao Created Date: 3/29/2006 1:44:49 PM Document presentation format: On-screen Show
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Important
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Title: PowerPoint Presentation Author: Learning Agents Laboratory Last modified by: Gheorghe Tecuci Created Date: 10/16/2000 12:50:33 AM Document presentation format
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Compare the samples not just their means. Do a statistically ... Approximate statistical tests for comparing supervised classification learning algorithms. ...
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Efficient Text Categorization with a Large Number of Categories Rayid Ghani KDD Project Proposal Text Categorization How do people deal with a large number of classes?
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For some ML algorithms, a direct extension to the multiclass case may be ... Row separations: Each codeword should be well-separated in Hamming distance from ...
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Title: PowerPoint Presentation Author: Learning Agents Laboratory Last modified by: Gheorghe Tecuci Created Date: 10/16/2000 12:50:33 AM Document presentation format
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Through the first half of the 20th century, most of the scientific community ... Term-weighting approaches in automatic text retrieval. Information Processing ...
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The agent receives a description of a cup that includes many features. ... if d connects r1 with r2 then it also connects r2 with r1. 28 ...
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Title: Diapositiva 1 Author: systems link International Last modified by: Soledad Bravo M. Created Date: 8/31/2006 11:30:34 AM Document presentation format
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Understand how to compare classification algorithms' performance. ... Comparing the expected errors of two algorithms: is k-NN more accurate than MLP ? ...
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Recognize faces, recognize speech, filter spam. Goals for today ... Spam filtering, terrain navigability (rovers) Classification ...
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Hierarchical Reinforcement Learning Amir massoud Farahmand Farahmand@SoloGen.net
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Let a' be an instance to classify. How to decide to which concept does a' belong? ... Each example is represented as a feature-value vector. ...
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A more basic decision than choice of representational framework is whether one ... These are most basic, best-studied induction tasks, which has led to development ...
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Generalize the found explanation as much as possible so that the proof still ... Let us consider again the explanation-based system learning an operational ...
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Output of unit: threshold (activation) function on net input (threshold = w0) ... Nonlinear activation (aka transfer, squashing) function: generalization of sgn ...
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Giving Advice about Preferred Actions to Reinforcement ... Lagoudakis and Parr, ICML 2003. Current and Future Work. Knowledge transfer via. preference advice ...
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Combining labeled and unlabeled data for text categorization with a large number of categories Rayid Ghani KDD Lab Project
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Revisiting Output Coding for Sequential Supervised Learning. Guohua Hao & Alan Fern. School of Electrical Engineering and Computer Science. Oregon State University ...
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The Winnow. Another linear threshold model. Learning algorithm and training rule ... Idea: use a Winnow - perceptron-type LTU model (Littlestone, 1988) ...
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Analogy maps the objects of the source onto the objects of the target: s1 ' t1, ... , sn ' tn ... Rainfall(Philippines, heavy), Terrain(Philippines, flat) ...
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Boosting approach, definition, characteristics. Early Boosting Algorithms ... constructing ensembles of decision trees: Bagging, boosting, and randomization. ...
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Which are the advantages of the instance-based learning algorithms? ... Exercise. Suggest a lazy version of the eager decision tree learning algorithm ID3. ...
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Dynamic Integration of Virtual Predictors Vagan Terziyan Information Technology Research Institute, University of Jyvaskyla, FINLAND e-mail: vagan@it.jyu.fi
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Increasing predicative accuracy. Reducing complexity of learned results. 4. Problem Statement. A process of selecting a minimum subset of features that is ...
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Start at the bottom left ... the bottom left, go to the top left, then over to the top right. A random prediction curve would be a line from the bottom left to ...
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An Introduction to Reinforcement Learning (Part 2) Jeremy Wyatt Intelligent Robotics Lab School of Computer Science University of Birmingham
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Sustainability and Sustainable Development ... Introduced the notion of sustainability and sustainable development: ... research in Computational Sustainability ...
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