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Supervised learning
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#	Item
61	Zodiac: Organizing Large Deployment of Sensors to Create Reusable Applications for Buildings Bharathan Balaji† , Chetan Verma† , Balakrishnan Narayanaswamy† , Yuvraj Agarwal‡ † † Add to Reading List Source URL: mesl.ucsd.edu Language: English - Date: 2015-09-15 22:49:21 Machine learning Systems science Information technology Information Data management Business intelligence Knowledge representation Records management Hierarchical clustering Semi-supervised learning Building automation Control system
62	Air pollution prediction via multi-label classification Giorgio Corani and Mauro Scanagatta Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA) Scuola universitaria professionale della Svizzera italiana Add to Reading List Source URL: ipg.idsia.ch Language: English - Date: 2016-04-26 02:11:02 Statistics Statistical classification Multivariate statistics Naive Bayes classifier Bayesian network Feature selection Bayes classifier Dependent and independent variables Machine learning Supervised learning K-nearest neighbors algorithm
63	Better Classifier Chains for Multi-label Classification Jesse Read, Fernando P´erez Cruz Department of Signal Theory and Communications Universidad Carlos III Madrid, Spain Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2011-07-21 06:05:16 Machine learning Classifier chains Statistical classification Multi-label classification Classifier Supervised learning Cognition Information
64	Efficient Online Evaluation of Big Data Stream Classifiers Albert Bifet Gianmarco De Francisci Morales Add to Reading List Source URL: melmeric.files.wordpress.com Language: English - Date: 2015-06-10 09:25:43 Machine learning Artificial intelligence Learning Statistics Multi-label classification Boosting Statistical classification Resampling Bootstrapping Supervised learning Pattern recognition Cross-validation
65	Kleinetal2012NCPW_revision.dvi Add to Reading List Source URL: www.stefanfrank.info Language: English - Date: 2013-05-22 07:20:36 Artificial neural networks Learning Artificial intelligence Applied mathematics Perceptron Multilayer perceptron Restricted Boltzmann machine Backpropagation Pattern recognition Boltzmann machine Delta rule Supervised learning
66	Chapter 2 I nducti ve Learni ng This chapter presents an overview of the research in inductive learning. We briefly describe the various aspects of this scientific field and present some examples of applications. We the Add to Reading List Source URL: www.dcc.fc.up.pt Language: English - Date: 2012-12-13 10:18:43 Machine learning Cognition Knowledge Learning Supervised learning Inductive logic programming Decision tree learning Inductive reasoning Artificial neural network Statistics Inference Book:Machine Learning The Complete Guide
67	Optimal Gradient-Based Learning Using Importance Weights Sepp Hochreiter and Klaus Obermayer Bernstein Center for Computational Neuroscience and Technische Universit¨at Berlin Add to Reading List Source URL: www.bioinf.jku.at Language: English - Date: 2013-01-23 02:39:45 Artificial neural networks Artificial intelligence Learning Applied mathematics Recurrent neural network Long short-term memory Sepp Hochreiter Backpropagation Vanishing gradient problem Supervised learning Support vector machine Generalization error
68	Supervised Pattern Classification Using Optimum-Path Forest Jo˜ao Paulo Papa and Alexandre Xavier Falc˜ao University of Campinas Institute of Computing Campinas, S˜ao Paulo - Brazil {papa.joaopaulo,alexandre.falcao}@g Add to Reading List Source URL: www.matmidia.mat.puc-rio.br Language: English - Date: 2009-12-09 18:55:18 Statistical classification Learning Data Cognition Support vector machine Classifier Margin classifier K-nearest neighbors algorithm Supervised learning Naive Bayes classifier Machine learning
69	Machine Learning Recap of main issues/phases Phases/problems in designing a ML algorithm •  Add to Reading List Source URL: twiki.di.uniroma1.it Language: English - Date: 2016-02-12 09:34:25 Machine learning Artificial intelligence Learning Cognition Unsupervised learning Supervised learning Reinforcement learning Learning classifier system
70	Classification and Learning for Character Recognition: Comparison of Methods and Remaining Problems Cheng-Lin Liu National Laboratory of Pattern Recognition (NLPR) Institute of Automation, Chinese Academy of Sciences P.O Add to Reading List Source URL: www.dsi.unifi.it Language: English - Date: 2009-12-17 04:49:49 Statistical classification Artificial intelligence Statistics Learning Machine learning Pattern recognition Support vector machine Supervised learning MNIST database Linear discriminant analysis Multiclass classification Perceptron