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Decision tree
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#	Item
81	Decision tree for Linking Project Records to the UPDB (RGE Application, Section 7, Question114300Answer “No” to Question 1 and proceed to Question 2. 020000Answer “No” to Question 1 and proceed to Que Add to Reading List Source URL: rge.utah.edu Language: English - Date: 2015-09-01 12:21:48
82	Property Testing: A Learning Theory Perspective Dana Ron∗ School of EE Tel-Aviv University Ramat Aviv, Israel Add to Reading List Source URL: www.eng.tau.ac.il Language: English - Date: 2009-05-02 11:33:29 Machine learning Computational complexity theory Theoretical computer science Applied mathematics Learning Models of computation Property testing Decision tree model Sample complexity PP Probability distribution Time complexity
83	Decision Tree Revised July 7, 2015 What instrument do you want to amplify? Add to Reading List Source URL: acousticimg.com Language: English - Date: 2015-07-13 16:02:37
84	University of California Santa Cruz CANRA Decision Tree Identification of Mandated Reporters Start Here Add to Reading List Source URL: shr.ucsc.edu Language: English - Date: 2014-09-11 16:17:54
85	mouth care product decision tree versAlternate Version2 Add to Reading List Source URL: files.www.mouthcarewithoutabattle.org Language: English - Date: 2013-01-25 10:46:16
86	mouth care product decision tree versAlternate Version2 Add to Reading List Source URL: files.www.mouthcarewithoutabattle.org Language: English Oral hygiene Dentifrices Antiseptics Dosage forms Listerine Chlorhexidine Dental caries Fluoride Toothpaste Biotene Mouthwash
87	Decision tree for nasogastric tube placement checks in CHILDREN and INFANTS (NOT NEONATES) Estimate NEX measurement (Place exit port of tube at tip of nose. Extend tube to earlobe, and then to xiphisternum) Insert fully Add to Reading List Source URL: rightbiometrics.com Language: English - Date: 2014-02-18 17:09:47
88	What do decision tree predictions look like in feature space? class 2 class 1 Add to Reading List Source URL: learning.eng.cam.ac.uk - Date: 2013-12-04 05:44:06
89	2.2 Counting Outcomes Overview of the lesson plan: Is it necessary to play a game many times to figure out the likelihood of winning? If not, how can we measure this likelihood? In this lesson, students learn that they c Add to Reading List Source URL: www.citydigits.org Language: English - Date: 2016-01-13 14:16:54 Teaching Education Learning Cognition Outcome Probability Decision tree Lesson Randomness
90	A Decision Tree Framework for Spatiotemporal Sequence Prediction Taehwan Kim Yisong Yue Add to Reading List Source URL: www.yisongyue.com Language: English - Date: 2015-06-03 14:15:40 Machine learning Conditional random field Structured prediction Hidden Markov model Artificial neural network Dynamic programming Decision tree learning Pattern recognition Recursion Supervised learning

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