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Model selection
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#	Item
41	Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool arXiv:1607.08878v1 [cs.NE] 29 Jul 2016 Add to Reading List Source URL: arxiv.org Language: English - Date: 2016-07-31 20:28:45 Artificial intelligence Machine learning Learning Mathematical optimization Model selection Ensemble learning Cybernetics Hyperparameter optimization Supervised learning Pipeline K-nearest neighbors algorithm Boosting
42	Inference, Models and Simulation for Complex Systems Lecture 5 Prof. Aaron Clauset 1 Add to Reading List Source URL: tuvalu.santafe.edu Language: English - Date: 2011-09-09 13:51:36 Statistics Statistical theory Model selection Estimation theory Bayesian statistics Probability distributions Likelihood function Maximum likelihood estimation Likelihood-ratio test Akaike information criterion Marginal likelihood Bayes factor
43	Optimal models of prosodic prominence using the Bayesian information criterion Tim Mahrt, Jui-Ting Huang, Yoonsook Mo, Margaret Fleck, Mark Hasegawa-Johnson, and Jennifer Cole Beckman Institute, University of Illinois Add to Reading List Source URL: prosody.beckman.illinois.edu Language: English - Date: 2012-08-16 01:03:16 Statistics Linguistics Systemic functional linguistics Statistical theory Phonology Model selection Phonetics Prosody Bayesian information criterion Topographic prominence Normal distribution Intonation
44	Genome Informatics 13: 51–A Comparative Study on Feature Selection and Classification Methods Using Gene Expression Profiles Add to Reading List Source URL: www.jsbi.org Language: English - Date: 2002-12-09 05:53:38 Machine learning Artificial intelligence Learning Statistical classification Search algorithms Model selection Ensemble learning Support vector machine K-nearest neighbors algorithm Feature selection Pattern recognition Polynomial kernel
45	Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves Add to Reading List Source URL: ijcai.org Language: English - Date: 2016-02-13 07:15:40 Artificial intelligence Computational neuroscience Artificial neural networks Applied mathematics Cognitive science Machine learning Cybernetics Model selection Convolutional neural network Hyperparameter optimization Deep learning MNIST database
46	Model selection Large scale model selection Summary and open problems Model Selection and Computational Oracle Inequalities for Large Scale Problems Add to Reading List Source URL: mmds-data.org Language: English - Date: 2016-03-09 01:29:53 Statistics Econometrics Statistical theory Estimation theory Linear regression Regression analysis Feature selection Model selection Support vector machine Oracle Database Loss function Natural selection
47	Early Warning Systems for Large Earthquakes: Classification of Near-source and Far-source Stations by using the Bayesian Model Class Selection M. Yamada, T.H. Heaton & J.L. Beck California Institute of Technology, Pasade Add to Reading List Source URL: www.eqh.dpri.kyoto-u.ac.jp Language: English - Date: 2009-05-21 20:56:28 Statistics Statistical theory Statistical models Bayesian network Networks Bayesian inference Earthquake Model selection Regression analysis
48	Theoretical Population Biology 62, 9–doi:tpbi, available online at http://www.idealibrary.com on Mutation–Selection Balance: Ancestry, Load, and Maximum Principle Add to Reading List Source URL: www.mabs.at Language: English - Date: 2007-11-28 06:43:27 Biology Evolutionary biology Population genetics Genetics Sexual selection Mutation Robustness Neutral mutation Error threshold Consonant mutation Natural selection Stepwise mutation model
49	Unsupervised Learning with Optimal Kernels Sepp Hochreiter and Klaus Obermayer Technische Universit¨at Berlin Abstract We investigate the optimal kernel for sample-based model selection in unsupervised learning if maxim Add to Reading List Source URL: www.bioinf.jku.at Language: English - Date: 2013-01-23 02:37:15 Machine learning Nonparametric statistics Time series analysis Estimation theory Kernel density estimation Sepp Hochreiter Supervised learning Linux kernel Kernel Estimator