>From the archives, it seems like there's some ongoing work to implement GLMs in PSPP. From the peanut gallery (hi!), it'd be nice if PSPP could interface with liblinear. It implements some GLM-like algorithms, see
http://www.csie.ntu.edu.tw/~cjlin/liblinear/ LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized classifiers L2-loss linear SVM, L1-loss linear SVM, and logistic regression (LR) L1-regularized classifiers (after version 1.4) L2-loss linear SVM and logistic regression (LR) L2-regularized support vector regression (after version 1.9) L2-loss linear SVR and L1-loss linear SVR. 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, Python, Ruby interfaces _______________________________________________ pspp-dev mailing list pspp-dev@gnu.org https://lists.gnu.org/mailman/listinfo/pspp-dev
