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Decision tree learning
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#	Item
91	software review Deeper into the Trees A new hybrid CHAID application analyzes multiple dependent variables. By Ken Deal Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2006-09-05 12:48:55 Regression analysis CHAID Market research Marketing Product management SPSS Latent class model Market segmentation Decision tree learning Statistics Computational statistics Decision trees
92	A Course in Machine Learning Hal Daumé III 10 \| L EARNING T HEORY Add to Reading List Source URL: ciml.info Language: English - Date: 2014-09-24 16:08:31 Computational learning theory Machine learning Models of computation Computational complexity theory Probably approximately correct learning Algorithm Decision tree model VC dimension PP Theoretical computer science Applied mathematics Mathematics
93	Structured Forests for Fast Edge Detection Piotr Doll´ar Microsoft Research C. Lawrence Zitnick Microsoft Research Add to Reading List Source URL: vision.ucsd.edu Language: English - Date: 2013-10-13 20:52:33 Artificial intelligence Imaging Vision Segmentation Edge detection Pedestrian detection Supervised learning Object recognition Decision tree learning Computer vision Image processing Machine learning
94	Microsoft Word - Using Decision Trees for Segmentation and Prediction by Outsource Research.doc Add to Reading List Source URL: www.orconsulting.com Language: English - Date: 2010-07-14 12:23:24 Machine learning Computational statistics Regression analysis CHAID Decision tree learning Scientific method Segmentation Statistical classification Statistics Decision trees Information
95	LNAIAlgorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2005-10-29 19:18:31 Data analysis Data mining Cybernetics Learning Decision tree learning Support vector machine Oracle Data Mining Supervised learning Statistics Machine learning Computational statistics
96	LNAIA Multi-relational Decision Tree Learning Algorithm - Implementation and Experiments Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2005-02-05 20:22:32 Data Data mining SQL Graph theory Decision tree learning Graph Table Relational database Database Data management Database theory Database management systems
97	A Framework for Learning from Distributed Data Using Sufficient Statistics and its Application to Learning Decision Trees Doina Caragea, Adrian Silvescu and Vasant Honavar Artificial Intelligence Research Laboratory, Com Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2004-01-12 12:32:02 Decision trees Data mining Data analysis Decision tree learning Distributed algorithm Algorithm Statistical classification Supervised learning Oracle Data Mining Machine learning Computational statistics Artificial intelligence
98	Decision Tree Induction from Distributed Heterogeneous Autonomous Data Sources Doina Caragea, Adrian Silvescu, and Vasant Honavar Artiﬁcial Intelligence Research Laboratory, Computer Science Department, Iowa State Univ Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2003-06-08 17:35:21 Artificial intelligence Data mining Theoretical computer science Data analysis Decision tree learning Algorithm Distributed algorithm ID3 algorithm R-tree Machine learning Decision trees Computational statistics
99	Microsoft Word - icml2003final06-02.doc Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2003-06-07 20:04:41 Machine learning Computational statistics Attribute grammar Compiler construction Parsing EXPRESS Attribute Decision tree learning Decision trees Computing Software engineering
100	Classification and Trees Luc Devroye School of Computer Science, McGill University Montreal, Canada H3A 2K6 This paper is dedicated to the memory of Pierre Devijver. Add to Reading List Source URL: www.ee.surrey.ac.uk Language: English - Date: 2011-07-07 10:04:15 Decision trees Ensemble learning Random forest Decision tree learning Statistical classification Perceptron Machine learning Computational statistics Artificial intelligence

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