Commit graph

4 commits

Author SHA1 Message Date
jperkin
5ac8723249 Build blas.a using libtool, fixes build on SunOS. Bump PKGREVISION. 2016-01-28 11:34:48 +00:00
adam
46f42a11c5 Changes 2.1:
Unknown
2015-11-20 14:47:20 +00:00
agc
286ea2536c Add SHA512 digests for distfiles for math category
Problems found locating distfiles:
	Package dfftpack: missing distfile dfftpack-20001209.tar.gz
	Package eispack: missing distfile eispack-20001130.tar.gz
	Package fftpack: missing distfile fftpack-20001130.tar.gz
	Package linpack: missing distfile linpack-20010510.tar.gz
	Package minpack: missing distfile minpack-20001130.tar.gz
	Package odepack: missing distfile odepack-20001130.tar.gz
	Package py-networkx: missing distfile networkx-1.10.tar.gz
	Package py-sympy: missing distfile sympy-0.7.6.1.tar.gz
	Package quadpack: missing distfile quadpack-20001130.tar.gz

Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden).  All existing
SHA1 digests retained for now as an audit trail.
2015-11-03 23:33:26 +00:00
cheusov
aa901feeca Add 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
2014-10-19 09:57:21 +00:00