https://www.bibsonomy.org/user/hotho/regressionBibSonomy RSS Feed for /user/hotho/regressionhttp://ccsl.mae.cornell.edu/eureqahotho2009-12-04T19:59:30+01:00analysis data equation learning regression tool <a itemprop="url" data-versiondate="2009-12-04T19:59:30+01:00" href="http://ccsl.mae.cornell.edu/eureqa" rel="nofollow" class="description-link">http://ccsl.mae.cornell.edu/eureqa</a>LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. Main features of LIBLINEAR include * Same data format as LIBSVM, our general-purpose SVM solver, and also similar usage * Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer * Cross validation for model selection * Probability estimates (logistic regression only) * Weights for unbalanced data * MATLAB/Octave, Java interfaceshttp://www.csie.ntu.edu.tw/~cjlin/liblinear/hotho2009-06-07T11:09:14+02:00classification fast liblinear library multilabel regression svm tools <span itemprop="description">LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. Main features of LIBLINEAR include * Same data format as LIBSVM, our general-purpose SVM solver, and also similar usage * Multi-class classification: 1) one-vs-the rest, 2) Crammer &amp; Singer * Cross validation for model selection * Probability estimates (logistic regression only) * Weights for unbalanced data * MATLAB/Octave, Java interfaces</span>http://www.stat.rutgers.edu/~madigan/BBR/hotho2005-03-14T13:50:20+01:00Bayesian Logistic Software Regression <a itemprop="url" data-versiondate="2005-03-14T13:50:20+01:00" href="http://www.stat.rutgers.edu/~madigan/BBR/" rel="nofollow" class="description-link">http://www.stat.rutgers.edu/~madigan/BBR/</a>