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Linear classifier
Results: 393

#	Item
341	A Few Useful Things to Know about Machine Learning Pedro Domingos Department of Computer Science and Engineering University of Washington Seattle, WA[removed], U.S.A. Add to Reading List Source URL: homes.cs.washington.edu Language: English - Date: 2012-09-28 02:35:50 Statistical classification Ensemble learning Boosting Linear classifier Overfitting Support vector machine Naive Bayes classifier Training set Supervised learning Statistics Machine learning Artificial intelligence
342	Tackling the Poor Assumptions of Naive Bayes Text Classifiers Jason D. M. Rennie [removed] Lawrence Shih [removed] Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2003-07-07 07:12:57 Machine learning Naive Bayes classifier Multiclass classification Linear classifier Document classification Classification rule Random naive Bayes Averaged one-dependence estimators Statistics Statistical classification Bayesian statistics
343	436 Chapter 12 Large-Scale Machine Learning Add to Reading List Source URL: infolab.stanford.edu Language: English - Date: 2014-05-28 15:45:03 Artificial intelligence Perceptron Supervised learning Neural network Training set Binary classification Linear classifier Margin classifier Statistics Machine learning Statistical classification
344	Condensed Filter Tree for Cost-Sensitive Multi-Label Classification Chun-Liang Li R[removed]@ CSIE . NTU . EDU . TW Hsuan-Tien Lin HTLIN @ CSIE . NTU . EDU . TW Department of Computer Science and Information Engineering, Add to Reading List Source URL: jmlr.org Language: English - Date: 2014-02-16 19:30:21 Artificial intelligence Multi-label classification Linear classifier Multiclass classification Classifier chains Support vector machine Structured SVM K-nearest neighbor algorithm Pattern recognition Machine learning Statistics Statistical classification
345	Hybrid Generative-Discriminative Classification using Posterior Divergence Xiong Li Shanghai Jiao Tong University Shanghai, 200240, China Tai Sing Lee Add to Reading List Source URL: www.cnbc.cmu.edu Language: English - Date: 2011-07-22 17:05:55 Fisher information Kullback–Leibler divergence Fisher kernel Likelihood function Linear classifier Supervised learning Score Dimensional analysis Maximum likelihood Statistics Estimation theory Expectation–maximization algorithm
346	CHAPTER 6 Ovidiu Ivanciuc. Applications of Support Vector Machines in Chemistry. In: Reviews in Computational Chemistry, Volume 23, Eds.: K. B. Lipkowitz and T. R. Cundari. Wiley-VCH, Weinheim, 2007, pp. 291–400. Appl Add to Reading List Source URL: www.ivanciuc.org Language: English - Date: 2009-01-18 01:27:31 Support vector machines Least squares support vector machine Kernel methods Cross-validation Quantitative structure–activity relationship Supervised learning Linear classifier Kernel principal component analysis Shogun Statistics Machine learning Statistical classification
347	Feature Set Embedding for Incomplete Data Iain Melvin NEC Labs America Princeton, NJ [removed] Add to Reading List Source URL: david.grangier.info Language: English - Date: 2010-12-15 14:12:10 Machine learning Abstract algebra Statistical classification Linear algebra Data analysis Linear classifier Supervised learning Support vector machine Pattern recognition Algebra Statistics Mathematics
348	Discriminative Learning can Succeed where Generative Learning Fails ? Philip M. Long, a Rocco A. Servedio, b,∗,1 Hans Ulrich Simon c a Google, b Columbia Add to Reading List Source URL: www.phillong.info Language: English - Date: 2013-08-07 12:11:06 Applied mathematics Generative model Discriminative model Probably approximately correct learning Probabilistic method Algorithm PP Linear classifier Supervised learning Machine learning Statistics Mathematics
349	The Power of Localization for Efficiently Learning Linear Separators with Noise Pranjal Awasthi [removed] Maria Florina Balcan Add to Reading List Source URL: www.phillong.info Language: English - Date: 2014-03-07 12:21:42 Learning Machine learning Statistical classification Supervised learning Information theory Vector space Stability Linear classifier PP Algebra Mathematics Cybernetics
350	Text Categorization with Many Redundant Features: Using Aggressive Feature Selection to Make SVMs Competitive with C4.5 Evgeniy Gabrilovich [removed] Shaul Markovitch [removed] Add to Reading List Source URL: www.cs.technion.ac.il Language: English - Date: 2004-05-05 03:44:42 Model selection Data mining Document classification Knowledge representation Support vector machine Cross-validation Linear classifier Feature selection Kernel methods Statistics Machine learning Statistical classification

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