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Decision trees
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#	Item
171	40165_2014_10_Article 1..25 Add to Reading List Source URL: www.decisionanalyticsjournal.com Language: English Machine learning Decision trees Naive Bayes classifier Statistical classification Weka Artificial neural network Sampling Cluster analysis Random forest Statistics Data analysis Data mining
172	A Criticism of Healthy-years Equivalents PETER WAKKER, PhD The following questions describe the scope of this paper. When decision trees are used to analyze optimal decisions, should end nodes be evaluated on the basis o Add to Reading List Source URL: people.few.eur.nl Language: English - Date: 2015-03-11 05:15:43 Microeconomics Statistics Health economics Game theory Consumer theory Quality-adjusted life year Expected utility hypothesis Risk aversion Indifference curve Utility Decision theory Economics
173	Practical Lessons from Predicting Clicks on Ads at Facebook Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu∗, Tao Xu∗, Yanxin Shi∗, Antoine Atallah∗, Ralf Herbrich∗, Stuart Bowers, Joaquin Quiñonero Candel Add to Reading List Source URL: quinonero.net Language: English - Date: 2014-09-14 16:43:06 Ensemble learning Decision trees Statistical classification Model selection Linear classifier Gradient boosting Pay per click Feature selection Boosting Machine learning Statistics Artificial intelligence
174	An Extension of the CHAID Tree-based Segmentation Algorithm to Multiple Dependent Variables? Jay Magidson1 and Jeroen K. Vermunt2 1 2 Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2006-09-05 12:14:41 Econometrics Categorical data Psychometrics CHAID Latent class model Multinomial logit Decision tree learning Latent variable Factor analysis Statistics Regression analysis Decision trees
175	Introduction to Boosted Trees Tianqi Chen Oct Outline • Review of key concepts of supervised learning Add to Reading List Source URL: homes.cs.washington.edu Language: English - Date: 2015-05-06 23:13:25 Econometrics Decision trees Ensemble learning Supervised learning Regularization Gradient boosting Linear regression Logistic regression Random forest Statistics Regression analysis Machine learning
176	Foliage: Decision Trees of A Different Color Brett Borghetti October 10, 2007 Add to Reading List Source URL: outobox.cs.umn.edu Language: English - Date: 2007-10-12 11:00:42 T-tree Tree Attribute Computing Data Information gain in decision trees ID3 algorithm Decision trees Binary trees Artificial intelligence
177	Implementing Decision Trees and Forests on a GPU Toby Sharp Microsoft Research, Cambridge, UK Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2009-07-27 08:07:00 Computing Image processing Shader Segmentation High Level Shader Language Microsoft Direct3D Random forest Shading language Histogram Computer graphics 3D computer graphics Shading
178	Application of machine learning methods to spatial interpolation of environmental variables Add to Reading List Source URL: www.islab.ntua.gr Language: English - Date: 2015-02-05 08:18:26 Econometrics Data analysis Decision trees Kriging Regression analysis Data mining Variogram Linear regression Random forest Statistics Interpolation Geostatistics
179	From the Fruit, Nut & Vine Workshop Series: Workshop Series 2015 All Things Fruit Trees Workshop Add to Reading List Source URL: www.petercoppin.com Language: English - Date: 2015-04-13 09:39:20 Plant reproduction Land management Agronomy Grafting Pruning Ziziphus mauritiana Decision trees Agriculture Botany
180	Credit Scoring in R 1 of 45 Guide to Credit Scoring in R Add to Reading List Source URL: ftp.yz.yamagata-u.ac.jp Language: English - Date: 2009-10-08 13:21:02 Biostatistics Econometrics Statistical models Credit score Data mining Random forest Logistic regression Pruning Recursive partitioning Statistics Regression analysis Decision trees

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