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Ensemble learning
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#	Item
241	Artif Intell Rev:159–190 DOIs10462Machine learning: a review of classification and combining techniques S. B. Kotsiantis · I. D. Zaharakis · P. E. Pintelas Add to Reading List Source URL: www.cs.bham.ac.uk Language: English - Date: 2008-05-15 09:15:06 Decision trees Statistical classification Supervised learning Perceptron Winnow Feature selection Ensemble learning Support vector machine Pruning Machine learning Statistics Computational statistics
242	Feature engineering for semantic place prediction Add to Reading List Source URL: dl.dropboxusercontent.com Language: English Statistical classification Parts of speech Ensemble learning Linear classifier Support vector machine Supervised learning Classifier Random forest Accelerometer Machine learning Statistics Artificial intelligence
243	RF + RLSC Kari Torkkola Eugene Tuv Add to Reading List Source URL: clopinet.com Language: English - Date: 2003-12-15 18:03:14 Learning Ensemble learning Dimension reduction Feature selection Random forest Statistical classification Cross-validation Statistics Machine learning Model selection
244	Technical Discussion: Foundations of TreeNet(tm) For further infomation consult: http://www.salford-systems.com/treenet.html Greedy Function Approximation: A Gradient Boosting Machine Add to Reading List Source URL: docs.salford-systems.com Language: English - Date: 2012-06-18 00:47:46 Gradient boosting Mathematical optimization Multiplier Differential geometry Fourier transform Generalized extreme value distribution Mathematical analysis Fourier analysis Ensemble learning
245	Evolution of Regression IV: From OLS to GPS™, MARS®, CART®, TreeNet® and RandomForests® March 2013 Dan Steinberg Add to Reading List Source URL: media.salford-systems.com Language: English - Date: 2013-04-13 01:04:51 Econometrics Ensemble learning Machine learning Linear regression Random forest Nonlinear regression Decision tree learning Gradient boosting Statistics Regression analysis Decision trees
246	Technical DIscussion of TreeNet(tm) For further information consult: http://www.salford-systems.com/treenet.html Stochastic Gradient Boosting Jerome H. Friedman Add to Reading List Source URL: docs.salford-systems.com Language: English - Date: 2012-06-18 00:37:08 Gradient boosting Statistical inference Errors and residuals in statistics Normal distribution Regression analysis Variance AdaBoost Estimation theory Random forest Statistics Ensemble learning Decision trees
247	TreeNet Tree Ensembles and CART Decision Trees: A Winning Combination October 2012 Mikhail Golovnya Add to Reading List Source URL: media.salford-systems.com Language: English - Date: 2012-10-23 00:17:53 Salford Greater Manchester Statistics Regression analysis Artificial intelligence Learning Decision trees Ensemble learning Gradient boosting
248	Minimax Games with Bandits Manfred K. Warmuth† Department of Computer Science UC Santa Cruz [removed] Add to Reading List Source URL: web.eecs.umich.edu Language: English - Date: 2013-10-28 18:03:14 Decision theory Ensemble learning Game artificial intelligence Search algorithms Computational learning theory Weighted Majority Algorithm Minimax Boosting Multi-armed bandit Statistics Machine learning Artificial intelligence
249	Predicting tree mortality from growth data: how virtual ecologists can help real ecologists Add to Reading List Source URL: wunder.co.nz Language: English - Date: 2008-07-03 17:58:23 Population ecology Ensemble learning Estimation theory Linear regression Forest inventory Logistic regression Kullback–Leibler divergence Non-parametric statistics Selection cutting Statistics Regression analysis Econometrics
250	Machine Learning Classification over Encrypted Data Raphael Bost Raluca Ada Popa Stephen Tu Add to Reading List Source URL: www.internetsociety.org Language: English - Date: 2015-02-07 13:16:35 Machine learning Cryptography Ensemble learning Homomorphic encryption Paillier cryptosystem AdaBoost Naive Bayes classifier Linear classifier Perceptron Statistics Statistical classification Public-key cryptography

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