If the liblinear developers (or anyone) is interested in writing such an interface, I would gladly help them. I suspect it would have to be done as a completely separate exercise to the GLM command.
Have you some ideas how such an interface should work? To what kind of users
do you think this would be of interest? What level of expertise would they
need?
J'
On Mon, Apr 22, 2013 at 06:01:52PM +0000, Jack Tanner wrote:
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
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