svmwrapversion

Wrapper on top of libsvm-tools

Svmwrap can be used to train/test regressors using libsvm-tools.

(Scary) usage: usage: ./svmwrap -i <filename>: training set or DB to screen --feats <int>: number of features output file [--kernel <string>] choose kernel type {Lin|RBF|Sig|Pol} C in the loss function of epsilon-SVR; (0 <= epsilon <= max_i(|y_i|)) NLopt with MAX_ITER (global optim.) instead of grid-search (recommended: MAX_ITER >= 100) gamma (for RBF and Sig kernels) r for the Sig kernel ON instance-wise-normalization ON [0:1] scaling (NOT PRODUCTION READY) gnuplot of cross validation to not specifying -q random seed set portion (in [0.0:1.0]) from .AP files (atom pairs; will offset feat. indexes by 1) set (overrides -p) set (overrides -p) set (overrides -p) mode; use trained models mode; save trained models overwriting existing model file for best C scan #steps for SVR for best gamma ; also, implied by -e and --scan-e range for e (semantic=start:nsteps:stop) [--c-range <float,float,...>] explicit scan range for C (example='0.01,0.02,0.03') [--g-range <float,float,...>] explicit range for gamma (example='0.01,0.02,0.03') [--r-range <float,float,...>] explicit range for r (example='0.01,0.02,0.03')

AuthorFrancois Berenger
LicenseBSD-3-Clause
Published
Homepagehttps://github.com/UnixJunkie/svmwrap
Issue Trackerhttps://github.com/UnixJunkie/svmwrap/issues
Maintainerunixjunkie@sdf.org
Dependencies
Optional dependencies
Source [http] https://github.com/UnixJunkie/svmwrap/archive/v4.0.0.tar.gz
sha256=0904f363cd48ffc16f670e0d0a6b7bc45992a463daff7ef1443b65e9980dc6e6
md5=faa68465c3574c9e1550e9c7bb1b7234
Edithttps://github.com/ocaml/opam-repository/tree/master/packages/svmwrap/svmwrap.4.0.0/opam
No package is dependent