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The Learning Tree
Results: 269

#	Item
91	Tree Ensembles: The Power of Post-‐‑Processing December 2012 Dan Steinberg Add to Reading List Source URL: media.salford-systems.com Language: English - Date: 2012-12-18 01:15:43 Salford Greater Manchester Data mining Machine learning Regression analysis City of Salford Statistics Local government in England Salford
92	Designing Palaver Tree Online: Supporting Social Roles in a Community of Oral History Jason B. Ellis and Amy S. Bruckman College of Computing Georgia Institute of Technology Atlanta, GA[removed]USA Add to Reading List Source URL: jellis.org Language: English - Date: 2011-04-27 21:55:10 Nelson Mandela Peter Gabriel The Elders Christianity American Indian elder Knowledge Elder Online community E-learning Education Social information processing Jimmy Carter
93	Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation Add to Reading List Source URL: www.aaai.org Language: English - Date: 2006-01-11 02:16:24 Computational statistics Formal sciences Learning Data analysis Cybernetics Hierarchy Decision tree learning Knowledge representation and reasoning Database Machine learning Science Data mining
94	From: Proceedings of the Third International Conference on Multistrategy Learning. Copyright © 1996, AAAI (www.aaai.org). All rights reserved. Fusing the Results of Diverse Algorithms John F. Elder IV, Ph.D. Elder Cons Add to Reading List Source URL: www.aaai.org Language: English - Date: 2006-01-11 11:06:53 Artificial intelligence Computational neuroscience Computational statistics Decision trees Decision tree learning Perceptron K-nearest neighbor algorithm Statistical classification Group method of data handling Machine learning Statistics Neural networks
95	[removed]Machine Learning, Spring 2011: Homework 1 Solution February 1, 2011 Instructions There are 3 questions on this assignment. The last question involves coding. Attach your code to the writeup. Please submit your hom Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2011-02-03 13:54:19 Decision trees Poisson processes Pruning Poisson distribution Kullback–Leibler divergence Tree Normal distribution Weight Gamma distribution Statistics Mathematical analysis Mathematics
96	What Do Kids Learn from Adults Online? Examining Student-Elder Discourse in Palaver Tree Jason B. Ellis & Amy S. Bruckman Georgia Institute of Technology {jellis, asb}@cc.gatech.edu ABSTRACT Add to Reading List Source URL: jellis.org Language: English - Date: 2011-04-27 21:55:10 Peter Gabriel The Elders Christianity Botany Sambucus Elder E-learning Education Jimmy Carter Nelson Mandela
97	FEE / Learning about Forests FEEs Global Forest Fund Application Form 2015 The FEE Global Forest Fund Application form must be sent to the International LEAF Director E-mail: [removed] Add to Reading List Source URL: www.green-key.org Language: English - Date: 2014-12-01 08:06:41 Learning about Forests Environmentalism Tree planting Bank Eco-Schools Land management Earth Young Reporters for the Environment Foundation for Environmental Education Environment Trees Environmental education
98	This file was created by scanning the printed publication. Text errors identified by the software have been corrected: however some errors may remain. Mapping wildland fuels and forest structure for land management: a co Add to Reading List Source URL: www.fs.fed.us Language: English - Date: 2013-03-28 14:45:20 Science Ecology Fire Natural hazards Occupational safety and health Leaf Area Index Fuel model Decision tree learning Wildfire Statistics Biology Ecological succession
99	The Boundary Forest Algorithm for online supervised and unsupervised learning Charles Mathy Nate Derbinsky Disney Research Boston Wentworth Institute of Technology Add to Reading List Source URL: www.disneyresearch.com Language: English - Date: 2015-01-19 20:27:41 Search algorithms R-tree K-d tree K-nearest neighbor algorithm Tree traversal Random forest Supervised learning Tango tree Interval tree Machine learning Artificial intelligence Mathematics
100	Estimating the Effect of Word of Mouth on Churn and Cross-Buying in the Mobile Phone Market with Markov Logic Networks Torsten Dierkes and Martin Bichler* Department of Informatics, TU München, Germany Ramayya Krishnan Add to Reading List Source URL: dss.in.tum.de Language: English - Date: 2011-01-10 10:15:53 Business intelligence Marketing Statistical relational learning Data mining Predictive modelling Customer lifetime value Decision tree learning Churn rate Probabilistic logic Statistics Statistical models Machine learning

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