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Random forest
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#	Item
231	Stratified sampling based on photointerpreted forest types reduces the cost of strategic forest inventory D.N. Thompson Forestry Tasmania in Forestry Tasmania can be found in the Add to Reading List Source URL: cdn.forestrytasmania.com.au Language: English - Date: 2007-10-08 00:32:46 Sample size determination Forest inventory Random sample Variance Analysis of variance Inventory Stratification Balanced repeated replication Horvitz–Thompson estimator Statistics Sampling Stratified sampling
232	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
233	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
234	Efficient Regression of General-Activity Human Poses from Depth Images Ross Girshick†? Jamie Shotton† Pushmeet Kohli† † Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2013-05-01 18:04:34 Computational statistics Random forest Regression analysis Tree Decision tree learning Object recognition Segmentation Decision trees Artificial intelligence Statistics
235	Bachelorarbeit Decision Forests for Regression Moritz Einfalt[removed] Add to Reading List Source URL: www.multimedia-computing.de Language: English - Date: 2014-12-02 06:09:53 Decision trees Ensemble learning Random forest Linear regression Predictive Model Markup Language Decision tree learning Statistics Regression analysis Econometrics
236	1 Film Classification by Trailer Features Edmund Helmer and Qinghui Ji December 14, 2012 Add to Reading List Source URL: cs229.stanford.edu Language: English - Date: 2013-01-09 19:55:28 Learning Bayesian statistics Ensemble learning Naive Bayes classifier Random forest Motion Picture Association of America film rating system Trailer Pattern recognition Support vector machine Statistics Statistical classification Machine learning
237	Desai et al. BMC Medicine 2014, 12:20 http://www.biomedcentral.com[removed]Medicine for Global Health RESEARCH ARTICLE Add to Reading List Source URL: www.cghr.org Language: English - Date: 2014-02-20 13:31:33 Random forest Ihme Health Autopsy Geographic information system Learning Global health Institute for Health Metrics and Evaluation Medicine
238	dual, 97 leave-one-out, 86 parametric, 84, 95 reproducibility index, 54, 79 sample, 76, 81, 115 Boxplot, 77 Add to Reading List Source URL: media.wiley.com Language: English - Date: 2012-03-15 07:17:04 Parametric statistics Evaluation methods Research methods Resampling Bootstrapping Functional magnetic resonance imaging Random forest Analysis of variance Statistical power Statistics Statistical tests Statistical inference
239	Object Class Segmentation using Random Forests F. Schroff1 , A. Criminisi2 , A. Zisserman1 1 Dept. of Engineering Science, University of Oxford {schroff,az}@robots.ox.ac.uk 2 Microsoft Research Ltd., [removed] Add to Reading List Source URL: www.bmva.org Language: English - Date: 2012-02-07 06:35:38 Statistics Vision Image processing Ensemble learning Histogram of oriented gradients Segmentation Linear classifier Color histogram Random forest Computer vision Artificial intelligence Machine learning
240	Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2010-06-07 17:10:14 Regression analysis Model selection Statistical classification Linear discriminant analysis Bayesian information criterion Feature selection Discriminant Principal component analysis Random forest Statistics Multivariate statistics Econometrics

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