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Ensemble learning
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#	Item
191	Minimal Cost Complexity Pruning of Meta-Classifiers Andreas L. Prodromidis Salvatore J. Stolfo Department of Computer Science Columbia University Add to Reading List Source URL: idm-lab.org Language: English - Date: 2005-05-31 06:09:24 Learning Artificial intelligence Ensemble learning Pruning Naive Bayes classifier Classifier Random subspace method AdaBoost Statistics Machine learning Statistical classification
192	11th International Society for Music Information Retrieval Conference (ISMIRA CARTESIAN ENSEMBLE OF FEATURE SUBSPACE CLASSIFIERS FOR MUSIC CATEGORIZATION T. Lidy, R. Mayer, A. Rauber Vienna University of Technolo Add to Reading List Source URL: ismir2010.ismir.net Language: English - Date: 2014-01-23 13:05:26 Statistical classification Learning Ensemble learning Information retrieval AdaBoost Support vector machine International Society for Music Information Retrieval Feature selection Classifier Statistics Artificial intelligence Machine learning
193	APPLICATION FOR INSTRUMENTAL LESSONS Students can apply to learn a musical instrument during school hours. Competency on an instrument opens a pathway for students to be eligible to join a music ensemble at TAS. TAS Conc Add to Reading List Source URL: www.tas.qld.edu.au Language: English - Date: 2015-01-21 19:38:58 Music education Music lesson Lesson Tutor Tuition agency Education Teaching Learning
194	Classification of Gene Expression Data on Public Clouds Christian Vecchiola1 , Mani Abedini, Michael Kirley, Xingchen Chu1 , and Rajkumar Buyya1 1 Cloud Computing and Distributed Systems (CLOUDS) Laboratory Dept. of Comp Add to Reading List Source URL: www.cloudbus.org Language: English - Date: 2009-08-28 00:34:04 Web services Statistical classification Machine learning Cloud infrastructure Ensemble learning Learning classifier system ADAPA Weka Distributed application Cloud computing Statistics Computing
195	WP_Koen_W_De_Bock_en_Dirk_Van_den_Poel1 Add to Reading List Source URL: www.feb.ugent.be Language: English - Date: 2012-09-09 17:15:49 Regression analysis Random subspace method Generalized additive model Statistical classification Learning classifier system Random forest Bootstrapping Feature selection Support vector machine Statistics Machine learning Ensemble learning
196	IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART C: APPLICATIONS AND REVIEWS, VOL. 31, NO. 4, NOVEMBERLearn++: An Incremental Learning Algorithm for Supervised Neural Networks Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2002-02-17 19:42:29 Statistical classification Learning AdaBoost Boosting Perceptron Multiclass classification Stability Boosting methods for object categorization Machine learning Ensemble learning Artificial intelligence
197	MICCLLR: Multiple-Instance Learning using Class Conditional Log Likelihood Ratio Yasser EL-Manzalawy1,2 and Vasant Honavar1 1 Department of Computer Science Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2009-07-11 21:20:08 Artificial intelligence Ensemble learning AdaBoost Support vector machine Boosting Multiple-instance learning Naive Bayes classifier Supervised learning Classifier Statistics Machine learning Statistical classification
198	Classification and Trees Luc Devroye School of Computer Science, McGill University Montreal, Canada H3A 2K6 This paper is dedicated to the memory of Pierre Devijver. Add to Reading List Source URL: www.ee.surrey.ac.uk Language: English - Date: 2011-07-07 10:04:15 Decision trees Ensemble learning Random forest Decision tree learning Statistical classification Perceptron Machine learning Computational statistics Artificial intelligence
199	NIPS03 Workshop: l1 -norm regularization l1 -norm Ji Zhu, Saharon Rosset, Trevor Hastie, Rob Tibshirani Add to Reading List Source URL: clopinet.com Language: English - Date: 2003-12-18 13:39:52 Linear algebra Statistical classification Mathematical analysis Regularization Tikhonov regularization AdaBoost Support vector machine Statistics Mathematics Ensemble learning
200	Assessing the Performance of Macromolecular Sequence Classifiers Cornelia Caragea, Jivko Sinapov, Vasant Honavar Drena Dobbs Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2007-09-25 17:18:34 Bioinformatics Bayesian statistics Cross-validation Model selection Ensemble learning Supervised learning Support vector machine Naive Bayes classifier Sequence alignment Statistics Machine learning Statistical classification

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