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Classifier
Results: 1687

#	Item
861	6.867 Machine learning, lecture 12 (Jaakkola) 1 Lecture topics: model selection criteria • Feature subset selection (cont’d) Add to Reading List Source URL: ocw.mit.edu Language: English - Date: 2015-03-15 16:36:56 Estimation theory Statistical theory Information theory Naive Bayes classifier Mutual information Likelihood function Loss function Statistics Bayesian statistics Statistical classification
862	CrossMark_Color_flat+click Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2014-02-03 01:46:37 Statistical classification Classifier Naive Bayes classifier Recommender system Supervised learning Binary classification Eigenvalues and eigenvectors Statistics Machine learning Algebra
863	Refined Experts Improving Classification in Large Taxonomies Paul N. Bennett Microsoft Research One Microsoft Way Redmond, WA Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2009-07-08 19:55:20 Support vector machine Hierarchy Tree structure Machine learning Linear classifier Binary classification Margin classifier Statistics Statistical classification Hierarchical classifier
864	Boilerplate Detection using Shallow Text Features Christian Kohlschütter, Peter Fankhauser, Wolfgang Nejdl L3S Research Center / Leibniz Universität Hannover Appelstr. 9a, 30167 Hannover Germany Add to Reading List Source URL: www.l3s.de Language: English - Date: 2014-06-25 04:22:58 Statistical classification Natural language processing Information retrieval Data mining Boilerplate Search engine indexing Random access machine Classification rule Classifier Statistics Information science Science
865	Infomation based supervised and semi-supervised feature selection Sang-Keun Lee, Seung-Joon Yi, Byoung-Tak Zhang School of Computer Science and Engineering Seoul National University Add to Reading List Source URL: clopinet.com Language: English - Date: 2003-12-10 06:27:48 Statistical classification Feature selection Machine learning Statistics Bayesian statistics Naive Bayes classifier
866	Estimating the accuracies of multiple classifiers without labeled data Ariel Jaffe Weizmann Institute of Science Boaz Nadler Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2015-03-25 10:37:42 Classifier Covariance Statistics Statistical classification Machine learning
867	Prospectivity of Western Australian iron ore from geophysical data using a reject option classifier Add to Reading List Source URL: earthbyte.org Language: English - Date: 2015-04-01 21:55:54 Yilgarn Craton Greenstone belt Pilbara craton Iron ore Exploration geophysics Ore Superior craton Goldsworthy Western Australia Aeromagnetic survey Geology Economic geology Mineral exploration
868	YAKHNENKO, O. AND HONAVAR, V.: MULTI-INSTANCE MULTI-LABEL LEARNING 1 Multi-Instance Multi-Label Learning for Image Classification with Large Vocabularies Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2011-08-29 20:36:54 Artificial intelligence Support vector machine Supervised learning Multiclass classification Margin classifier Multiple-instance learning Classifier chains Book:Machine Learning - The Complete Guide Statistics Machine learning Statistical classification
869	Feature engineering for semantic place prediction Add to Reading List Source URL: dl.dropboxusercontent.com Language: English Statistical classification Parts of speech Ensemble learning Linear classifier Support vector machine Supervised learning Classifier Random forest Accelerometer Machine learning Statistics Artificial intelligence
870	AVT-NBL: An Algorithm for Learning Compact and Accurate Na¨ıve Bayes Classifiers from Attribute Value Taxonomies and Data Jun Zhang and Vasant Honavar Artificial Intelligence Research Laboratory Department of Computer Add to Reading List Source URL: www.cs.iastate.edu Language: English - Date: 2005-10-30 21:58:22 Multiclass classification Classifier Classification rule Support vector machine Attribute Statistics Statistical classification Naive Bayes classifier

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