./math/crfsuite, Fast implementation of Conditional Random Fields (CRFs)

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Branch: CURRENT, Version: 0.12nb1, Package name: crfsuite-0.12nb1, Maintainer: cheusov

CRFSuite is an implementation of Conditional Random Fields (CRFs) for
labeling sequential data. The first priority of this software is to
train and use CRF models as fast as possible even at the expense of
its memory space and code generality. CRFsuite runs 5.4 - 61.8 times
faster than C++ implementations for training. CRFsuite supports
parameter estimation with L1 regularization (Laplacian prior) using
Orthant-Wise Limited-memory Quasi-Newton (OW-LQN) method and L2
regularization (Gaussian prior) using Limited-memory BFGS (L-BFGS)
method.


Required to run:
[lang/python27]

Required to build:
[pkgtools/cwrappers]

Master sites:


Version history: (Expand)


CVS history: (Expand)


   2015-11-04 00:33:46 by Alistair G. Crooks | Files touched by this commit (262)
Log message:
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.
   2015-03-31 17:49:15 by Joerg Sonnenberger | Files touched by this commit (1)
Log message:
SSE2 support only makes sense on X86, but configure doesn't really
check. Use a blunt object to help it.
   2014-10-31 01:54:02 by Aleksey Cheusov | Files touched by this commit (4)
Log message:
Include example scripts, some of the are rather useful.
++pkgrevision.
   2014-10-30 00:13:21 by Aleksey Cheusov | Files touched by this commit (9) | Imported package
Log message:
CRFSuite is an implementation of Conditional Random Fields (CRFs) for
labeling sequential data. The first priority of this software is to
train and use CRF models as fast as possible even at the expense of
its memory space and code generality. CRFsuite runs 5.4 - 61.8 times
faster than C++ implementations for training. CRFsuite supports
parameter estimation with L1 regularization (Laplacian prior) using
Orthant-Wise Limited-memory Quasi-Newton (OW-LQN) method and L2
regularization (Gaussian prior) using Limited-memory BFGS (L-BFGS)
method.