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Book:Machine Learning - The Complete Guide
Results: 76

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31	American Political Science Review Vol. 98, No. 2 May 2004 Add to Reading List Source URL: politicalscience.osu.edu Language: English - Date: 2013-01-02 17:53:03 Categorical data Statistical models Computational neuroscience Logistic regression Dummy variable Logit Neural network Forecasting Book:Machine Learning - The Complete Guide Statistics Econometrics Regression analysis
32	Low level information extraction a Bayesian network based approach Remco R. Bouckaert , Xtal Mountain Information Technology & Computer Science Department, University of Waikato, New Ze Add to Reading List Source URL: www.xm.co.nz Language: English - Date: 2002-05-29 01:05:46 Graphical model Statistical classification Naive Bayes classifier Supervised learning Markov blanket Bayesian inference Hidden Markov model Random naive Bayes Book:Machine Learning - The Complete Guide Statistics Bayesian statistics Bayesian network
33	Tom Minka Model-Based Machine Learning The Challenge  Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2013-05-16 08:19:25 Simulation Applied mathematics Algorithm Mathematics Science One-shot learning Book:Machine Learning - The Complete Guide Cybernetics Learning Machine learning
34	Semi-Supervised Structuring of Complex Data Marian-Andrei Rizoiu ERIC Laboratory, University Lumière, Lyon, France Main objectives Add to Reading List Source URL: www.rizoiu.eu Language: English - Date: 2013-10-04 10:30:17 Machine learning Natural language processing Knowledge Data mining Semantic Web Knowledge discovery Ontology Book:Machine Learning - The Complete Guide Unsupervised learning Science Artificial intelligence Knowledge representation
35	KERNEL METHODS MATCH DEEP NEURAL NETWORKS ON TIMIT Po-Sen Huang† , Haim Avron‡ , Tara N. Sainath‡ , Vikas Sindhwani‡ , Bhuvana Ramabhadran‡ † Department of Electrical and Computer Engineering, University of I Add to Reading List Source URL: www.ifp.illinois.edu Language: English - Date: 2014-03-11 17:55:13 Support vector machine Kernel trick Linux kernel Kernel methods Gaussian function Kernel Kernel adaptive filter Book:Machine Learning - The Complete Guide Statistics Statistical classification Machine learning
36	Important points to remember Machine learning is the systematic study of algorithms and systems that improve their knowledge or performance with experience. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Add to Reading List Source URL: www.cs.bris.ac.uk Language: English - Date: 2012-04-23 06:41:00 Linear classifier Receiver operating characteristic Margin classifier Calibration Overfitting Supervised learning Book:Machine Learning - The Complete Guide Statistics Statistical classification Naive Bayes classifier
37	Application of Matrix Clustering to Web Log Analysis and Access Prediction Shigeru Oyanagi, Kazuto Kubota and Akihiko Nakase Parallel Application TOSHIBA Laboratory, Real World Computing Partnership R&D Center, Toshiba C Add to Reading List Source URL: ai.stanford.edu Language: English - Date: 2001-07-19 13:34:58 Multivariate statistics Cluster analysis Matrix Association rule learning Book:Machine Learning - The Complete Guide Non-negative matrix factorization Statistics Data analysis Data mining
38	BENEFITS OF CREATING ENSEMBLES OF CLASSIFIERS Dean Abbott - Abbott Analytics Introduction In recent years, there has been an explosion of papers in the data mining community discussing how to combine models or model pred Add to Reading List Source URL: www.abbottanalytics.com Language: English - Date: 2010-08-10 08:15:57 Statistics Formal sciences Boosting Neural network Statistical classification Data mining Bootstrap aggregating Book:Machine Learning - The Complete Guide Machine learning Ensemble learning Artificial intelligence
39	Combining Models to Improve Classifier Accuracy and Robustness1 Dean W. Abbott Abbott Consulting P.O. Box[removed]San Diego, CA[removed]USA Email: [removed] Add to Reading List Source URL: www.abbottanalytics.com Language: English - Date: 2010-08-10 08:15:57 Ensemble learning Computational neuroscience Statistical classification Computational statistics Neural network Pattern recognition K-nearest neighbor algorithm Boosting Book:Machine Learning - The Complete Guide Machine learning Artificial intelligence Learning
40	Machine Learning on Spark Shivaram Venkataraman UC Berkeley Machine learning Add to Reading List Source URL: ampcamp.berkeley.edu Language: English - Date: 2013-02-27 07:37:26 Machine learning Cybernetics Learning Collaborative filtering Apache Hadoop K-means clustering Consensus clustering Book:Machine Learning - The Complete Guide Statistics Computational statistics Computing

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