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Ensemble learning
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#	Item
321	Using Boosted Features for the Detection of People in 2D Range Data Add to Reading List Source URL: www.service-robotik-initiative.de Language: English - Date: 2007-11-05 10:06:14 Statistics Learning Statistical classification Parts of speech Face recognition AdaBoost Classifier Viola–Jones object detection framework Boosting Artificial intelligence Ensemble learning Machine learning
322	Structure Learning with Hidden Data in Relational Domains Tushar Khot, Sriraam Natarajan∗ , Kristian Kersting∗+ , Jude Shavlik University of Wisconsin-Madison, USA ∗ Wake Forest University School of Medicine, USA Add to Reading List Source URL: www.first-mm.eu Language: English - Date: 2012-07-18 16:57:18 Model theory Statistical models Ensemble learning Gradient boosting Expectation–maximization algorithm Function First-order logic Regression analysis Supervised learning Statistics Mathematics Machine learning
323	Package ‘GAMBoost’ July 2, 2014 Version 1.2-3 Title Generalized linear and additive models by likelihood based boosting Author Harald Binder Maintainer Harald Binder Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 09:49:39 Model selection Machine learning Ensemble learning Degrees of freedom Proportional hazards models Akaike information criterion Cross-validation Boosting Generalized linear model Statistics Regression analysis Statistical models
324	Package ‘CoxBoost’ July 2, 2014 Version 1.4 Title Cox models by likelihood based boosting for a single survival endpoint or competing risks Author Harald Binder Maintainer Harald Binder Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 09:38:46 Machine learning Cross-validation Model selection Degrees of freedom Proportional hazards models Gradient boosting Boosting Null Matrix Statistics Regression analysis Ensemble learning
325	MLbase: A Distributed Machine Learning Wrapper Ameet Talwalkara, † Tim Kraskaa, † Rean Griffithb John Duchia Joseph Gonzaleza Denny Britza Xinghao Pana Virginia Smitha Evan Sparksa Andre Wibisonoa Michael J. Frankli Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2014-01-12 23:43:03 Ensemble learning Learning Information retrieval Cybernetics AdaBoost Static single assignment form Collaborative filtering Support vector machine Boosting Machine learning Statistics Computational statistics
326	Ensemble Methods for Personality Recognition Ben Verhoeven and Walter Daelemans and Tom De Smedt CLiPS, University of Antwerp Prinsstraat 13 (L), 2000 Antwerp, Belgium Abstract Add to Reading List Source URL: www.clips.ua.ac.be Language: English - Date: 2013-05-28 04:43:06 Artificial intelligence Ensemble learning Statistical classification Boosting Support vector machine Cross-validation Classifier Statistics Machine learning Learning
327	JMLR: Workshop and Conference Proceedings 29:1–16, 2013 ACML 2013 Random Projections as Regularizers: Learning a Linear Discriminant Ensemble from Fewer Add to Reading List Source URL: www.cms.waikato.ac.nz Language: English - Date: 2013-10-14 20:40:21 Ensemble learning Multivariate normal distribution Normal distribution Variance Random forest Covariance Statistics Data analysis Covariance and correlation
328	Boosting and Rocchio Applied to Text Filtering Robert E. Schapire, Yoram Singer, Amit Singhal AT&T Labs — Research 180 Park Avenue, Florham Park, NJ[removed]fschapire,singer,[removed] Abstract Add to Reading List Source URL: singhal.info Language: English - Date: 2007-08-16 20:14:07 Information Natural language processing Ensemble learning AdaBoost Machine learning Relevance feedback Boosting Precision and recall Vector space model Information science Information retrieval Science
329	Propositionalisation of Multi-instance Data using Random Forests Eibe Frank and Bernhard Pfahringer Department of Computer Science, University of Waikato {eibe,bernhard}@cs.waikato.ac.nz Add to Reading List Source URL: www.cms.waikato.ac.nz Language: English - Date: 2013-09-13 04:47:11 Decision trees Ensemble learning Weka Random forest Statistical classification Support vector machine Alternating decision tree Decision tree learning Machine learning Statistics Computational statistics
330	Perceptron Learning with Random Coordinate Descent Ling Li Learning Systems Group, California Institute of Technology Abstract. A perceptron is a linear threshold classifier that separates examples with a hyperplane. It Add to Reading List Source URL: authors.library.caltech.edu Language: English - Date: 2012-12-26 09:14:16 Perceptron Linear classifier Support vector machine Boosting AdaBoost Artificial neural network Ensemble learning Backpropagation Statistical classification Machine learning Statistics Neural networks

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