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Kernel method
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11	Ghostscript wrapper for X:ersV2011er_final.pdf Add to Reading List Source URL: www2.ece.ohio-state.edu Language: English - Date: 2011-08-09 10:09:19 Algebra Mathematics Linear algebra Numerical linear algebra Dimension reduction Functional analysis Multivariate statistics Linear map Singular value decomposition Kernel method Principal component analysis Kernel
12	Methods for Multi-Category Cancer Diagnosis from Gene Expression Data: A Comprehensive Evaluation to Inform Decision Support System Development Alexander Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos Discovery S Add to Reading List Source URL: www.dsl-lab.org Language: English - Date: 2004-02-18 20:07:17 Machine learning Learning Statistics Artificial intelligence Statistical classification Model selection Support vector machine Cross-validation K-nearest neighbors algorithm Ensemble learning Kernel method Pattern recognition
13	Appendix A. Introduction to Binary Support Vector Machines Below we summarize the main ideas behind binary Support Vector Machines via a short theoretical description followed by an example. For a detailed review of SVMs Add to Reading List Source URL: www.dsl-lab.org Language: English - Date: 2007-03-08 11:51:27 Statistical classification Learning Support vector machine Polynomial kernel Acute myeloid leukemia Kernel method Decision boundary Multiclass classification
14	Contents 1 Introduction 2 The Add to Reading List Source URL: www.bioinf.jku.at Language: English - Date: 2013-04-30 01:33:38 Algebra Mathematics Machine learning Linear algebra Statistical classification Support vector machines Matrices Matrix Kernel method Kernel Test set Linear map
15	1 Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer’s Disease through Automated Hippocampal Segmentation Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova, Amity E. Green, Arthur W. Toga, and Add to Reading List Source URL: pages.ucsd.edu Language: English - Date: 2010-04-14 20:51:16 Machine learning Artificial intelligence Learning Ensemble learning Statistical classification AdaBoost Support vector machine Boosting Kernel method Voxel Image segmentation Functional magnetic resonance imaging
16	Classiﬁcation, Regression, and Feature Selection on Matrix Data Sepp Hochreiter and Klaus Obermayer Department of Electrical Engineering and Computer Science Technische Universit¨at BerlinBerlin, Germany Add to Reading List Source URL: www.bioinf.jku.at Language: English - Date: 2013-04-30 01:33:38 Algebra Mathematics Linear algebra Abstract algebra Matrices Statistical classification Machine learning Support vector machine Matrix Test set Kernel method Kernel
17	Multiple Kernel Learning, Conic Duality, and the SMO Algorithm Francis R. Bach & Gert R. G. Lanckriet {fbach,gert}@cs.berkeley.edu Department of Electrical Engineering and Computer Science, University of California, Ber Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:00:25 Machine learning Learning Support vector machines Artificial intelligence Sequential minimal optimization Multiple kernel learning NC Kernel method KarushKuhnTucker conditions
18	Large-scale Learning with Kernels & libSkylark Vikas Sindhwani IBM Research, NY MMDSAlgorithms for Modern Massive Data Sets Add to Reading List Source URL: mmds-data.org Language: English - Date: 2014-06-19 15:38:22 Computing Concurrent computing Data Parallel computing Apache Hadoop Apache Software Foundation Cloud infrastructure Big data MapReduce Kernel method Lasso Integral transform
19	© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promo Add to Reading List Source URL: www.wjscheirer.com Language: English - Date: 2012-11-13 20:10:21 Learning Machine learning Artificial intelligence Statistical classification Support vector machine Kernel method Supervised learning Pattern recognition Semi-supervised learning Positive-definite kernel Binary classification Decision boundary
20	© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promo Add to Reading List Source URL: www.wjscheirer.com Language: English - Date: 2014-06-17 17:06:45 Statistics Learning Machine learning Statistical classification Support vector machines Statistical models Kernel method Probability distribution Platt scaling Pattern recognition Probability Bayesian network

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