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Decision tree learning
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#	Item
101	Boosting Flexible Learning Ensembles with Dynamic Feature Selection Add to Reading List Source URL: clopinet.com Language: English - Date: 2003-12-15 08:14:06 Econometrics Machine learning Decision tree learning Random forest Feature selection Linear regression Statistics Regression analysis Decision trees
102	Problem statement Objectives Time Series Split-test strategies Add to Reading List Source URL: ama.liglab.fr Language: English - Date: 2014-11-24 06:48:38 Education Science Data mining Image processing Decision tree learning Segmentation Statistical classification Test Statistical hypothesis testing Statistics Machine learning Psychometrics
103	Community consultation – tree root pruning Generally tree root pruning requests by the community are considered by the City of Port Phillip for potential conflicts between infrastructure and tree roots and where potent Add to Reading List Source URL: m.portphillip.vic.gov.au Language: English - Date: 2011-02-10 23:52:35 Fruit tree pruning Decision trees Pruning Learning
104	Salford Systems Critical Features of High performance Decision Trees Decision trees have justifiably become one of the most popular data mining tools. They are relatively easy to use, the results can usually be displayed Add to Reading List Source URL: media.salford-systems.com Language: English - Date: 2013-07-26 03:41:13 Artificial intelligence Decision tree learning Decision tree Pruning R-tree Data mining CHAID Decision trees Statistics Computational statistics
105	PLANET: Massively Parallel Learning of Tree Ensembles with MapReduce Biswanath Panda, Joshua S. Herbach, Sugato Basu, Roberto J. Bayardo Google, Inc. [bpanda, jsherbach, sugato]@google.com, [removed] Add to Reading List Source URL: static.googleusercontent.com Language: English - Date: 2012-04-01 20:13:23 Binary trees Machine learning Decision trees Distributed computing architecture MapReduce Parallel computing Decision tree learning Tree traversal B-tree Computing Concurrent computing Computer programming
106	Molecular Data Mining Tool: Advances In HIV Research he ability to predict biological activity based on molecular structure is leading researchers to breakthroughs in the most complex challenges of medicine. Using a Add to Reading List Source URL: media.salford-systems.com Language: English - Date: 2013-07-26 03:42:00 Econometrics Science Computational statistics Neural networks Artificial neural network Decision tree learning Multivariate adaptive regression splines Data mining Regression analysis Statistics Computational neuroscience Machine learning
107	Structured Forests for Fast Edge Detection Piotr Doll´ar Microsoft Research C. Lawrence Zitnick Microsoft Research Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2013-10-15 22:53:41 Artificial intelligence Imaging Vision Segmentation Edge detection Pedestrian detection Supervised learning Object recognition Decision tree learning Computer vision Image processing Machine learning
108	doi:[removed]j.biocon[removed] Add to Reading List Source URL: www.umass.edu Language: English - Date: 2009-09-07 14:25:17 Herpetology Spotted Salamander Vernal pool Marbled Salamander Ecology Frog Decision tree learning Amphibian Regression analysis Mole salamanders Statistics Water
109	Extracting Knowledge and Computable Models from Data - Needs, Expectations, and Experience ¨ Thomas Natschlager, Felix Kossak, and Mario Drobics Software Competence Center Hagenberg, A-4232 Hagenberg, Austria Add to Reading List Source URL: www.unisoftwareplus.com Language: English - Date: 2014-11-21 04:06:25 Machine learning Data mining Data analysis Formal sciences Computational neuroscience Pattern recognition Neural network Decision tree learning Mathematica Statistics Science Mathematical software
110	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 52, NO. 12, DECEMBER[removed]Evaluating Tree Detection and Segmentation Routines on Very High Resolution Add to Reading List Source URL: www.lucieer.net Language: English - Date: 2014-11-24 00:21:30 Data mining Decision trees LIDAR Robotic sensing Search algorithms Random forest Cluster analysis Algorithm K-nearest neighbor algorithm Machine learning Statistics Artificial intelligence

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