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Source: liblinear
Priority: optional
Maintainer: Christian Kastner <debian@kvr.at>
Build-Depends:
debhelper (>= 7.0.50~),
python-support (>= 0.90),
libblas-dev
Standards-Version: 3.9.0
Section: libs
Homepage: http://www.csie.ntu.edu.tw/~cjlin/liblinear/
Vcs-Git: git://scm.kvr.at/git/pkg-liblinear.git
Vcs-Browser: http://scm.kvr.at/git/?p=liblinear.git;a=summary
Package: liblinear-dev
Section: libdevel
Architecture: any
Depends:
${misc:Depends},
liblinear1 (= ${binary:Version}),
libblas-dev
Description: Development libraries and header files for LIBLINEAR
LIBLINEAR is a library for learning linear classifiers for large scale
applications. It supports Support Vector Machines (SVM) with L2 and L1
loss, logistic regression, multi class classification and also Linear
Programming Machines (L1-regularized SVMs). Its computational complexity
scales linearly with the number of training examples making it one of
the fastest SVM solvers around.
.
This package contains the header files and static libraries.
Package: liblinear1
Architecture: any
Depends:
${shlibs:Depends},
${misc:Depends}
Recommends:
liblinear-tools (= ${binary:Version})
Suggests:
liblinear-dev (= ${binary:Version})
Description: Library for Large Linear Classification
LIBLINEAR is a library for learning linear classifiers for large scale
applications. It supports Support Vector Machines (SVM) with L2 and L1
loss, logistic regression, multi class classification and also Linear
Programming Machines (L1-regularized SVMs). Its computational complexity
scales linearly with the number of training examples making it one of
the fastest SVM solvers around. It also provides Python bindings.
.
This package contains the shared libraries.
Package: liblinear-dbg
Priority: extra
Section: debug
Architecture: any
Depends:
${misc:Depends},
liblinear1 (= ${binary:Version}),
liblinear-tools (= ${binary:Version})
Description: Debugging symbols for LIBLINEAR
LIBLINEAR is a library for learning linear classifiers for large scale
applications. It supports Support Vector Machines (SVM) with L2 and L1
loss, logistic regression, multi class classification and also Linear
Programming Machines (L1-regularized SVMs). Its computational complexity
scales linearly with the number of training examples making it one of
the fastest SVM solvers around. It also provides Python bindings.
.
This package contains the debugging symbols.
Package: liblinear-tools
Section: science
Architecture: any
Depends:
${shlibs:Depends},
${misc:Depends},
liblinear1 (= ${binary:Version})
Recommends:
libsvm-tools
Description: Standalone applications for LIBLINEAR
LIBLINEAR is a library for learning linear classifiers for large scale
applications. It supports Support Vector Machines (SVM) with L2 and L1
loss, logistic regression, multi class classification and also Linear
Programming Machines (L1-regularized SVMs). Its computational complexity
scales linearly with the number of training examples making it one of
the fastest SVM solvers around. It also provides Python bindings.
.
This package contains the standalone applications.
Package: python-liblinear
Section: python
Architecture: any
Depends:
${python:Depends},
${misc:Depends},
liblinear1 (= ${binary:Version})
Description: Python bindings for LIBLINEAR
LIBLINEAR is a library for learning linear classifiers for large scale
applications. It supports Support Vector Machines (SVM) with L2 and L1
loss, logistic regression, multi class classification and also Linear
Programming Machines (L1-regularized SVMs). Its computational complexity
scales linearly with the number of training examples making it one of
the fastest SVM solvers around. It also provides Python bindings.
.
This package contains the Python bindings.
|
