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Cross-validation
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#	Item
301	Development and cross-validation of SNAP The perceived need The potential sources of confusion when seeking to identify a child’s specific learning difficulty are discussed in Section 1 of the SNAP User’s Kit, as is Add to Reading List Source URL: www.snapassessment.com Language: English - Date: 2005-06-01 06:45:12 Dyslexia Learning disabilities Childhood psychiatric disorders Developmental dyspraxia Dysgraphia Theory of multiple intelligences Reading Educational psychologist Attention deficit hyperactivity disorder Education Special education Educational psychology
302	Microsoft Word - aaai_paper10.doc Add to Reading List Source URL: www.aaai.org Language: English - Date: 2007-01-22 20:09:52 Machine learning Acronyms Diving equipment Sonar Speech recognition K-nearest neighbor algorithm Spectral density Cross-validation Science Statistics Signal processing Artificial intelligence
303	Predicting Listener Backchannels: A Probabilistic Multimodal Approach Louis-Philippe Morency1 , Iwan de Kok2 , and Jonathan Gratch1 1 Institute for Creative Technologies, University of Southern California, Add to Reading List Source URL: doc.utwente.nl Language: English - Date: 2011-08-28 13:39:54 Memory Model selection Linguistics Backchannel Ethology Encoding Hidden Markov model Feature selection Cross-validation Mind Statistics Mental processes
304	The cross-validation process Exploration of SNAP’s validity has been continuous, testing the emerging instrument at every stage on pupils whose difficulties were already known and well-documented. There were a number Add to Reading List Source URL: www.snapassessment.com Language: English - Date: 2005-06-01 06:45:10 Dyslexia Psychiatry Educational psychology Childhood psychiatric disorders Learning disabilities Developmental dyspraxia Auditory processing disorder Specific language impairment Attention deficit hyperactivity disorder Education Health Special education
305	Learning on the Test Data: Leveraging “Unseen” Features Ben Taskar BTASKAR @ CS . STANFORD . EDU Ming Fai Wong MINGFAI . WONG @ CS . STANFORD . EDU Add to Reading List Source URL: ai.stanford.edu Language: English - Date: 2005-10-04 19:13:52 Statistical models Statistical classification Model selection Overfitting Bayesian network Cross-validation Support vector machine Graphical model Naive Bayes classifier Statistics Bayesian statistics Machine learning
306	Phone Number Validation Version 3.0 WSDL: http://ws.strikeiron.com/StrikeIron/PhoneValidation3?WSDL Product Web Page: http://www.strikeiron.com/Catalog/ProductDetail.aspx?pv=3.0.0&pn=Phone%20Number%20Validation Add to Reading List Source URL: www.strikeiron.com Language: English - Date: 2014-02-17 11:00:45 Scripting languages Password Strikeiron HTML element JavaScript Computing Cross-platform software Software
307	Active Feature-Value Acquisition for Classifier Induction Prem Melville Dept. of Computer Sciences Univ. of Texas at Austin [removed] Add to Reading List Source URL: www.cs.utexas.edu Language: English - Date: 2004-10-13 12:26:03 Measurement Psychometrics Supervised learning Cross-validation Accuracy and precision Uncertainty Statistics Machine learning Statistical theory
308	Estimating treatment effect heterogeneity in randomized program evaluation Add to Reading List Source URL: imai.princeton.edu Language: English - Date: 2014-05-15 08:34:59 Design of experiments Model selection Evaluation methods Statistical power Average treatment effect Support vector machine Experiment Feature selection Cross-validation Statistics Econometrics Regression analysis
309	Continuous Conditional Neural Fields for Structured Regression Tadas Baltruˇsaitis1 , Peter Robinson1 , Louis-Philippe Morency2 1 Computer Laboratory, University of Cambridge, UK Add to Reading List Source URL: multicomp.ict.usc.edu Language: English - Date: 2014-08-08 23:16:28 Econometrics Categorical data Logistic regression Structured prediction Pattern recognition Cross-validation Support vector machine Statistics Regression analysis Machine learning
310	NeuroImage[removed]–100 Contents lists available at ScienceDirect NeuroImage j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / y n i m g Add to Reading List Source URL: compmem.princeton.edu Language: English - Date: 2011-05-30 14:04:47 Statistical models Magnetic resonance imaging Bayesian statistics Functional magnetic resonance imaging Mixture model Voxel Spatial analysis Conjugate prior Cross-validation Statistics Machine learning Neuroimaging

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