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|)) 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')
Author | Francois Berenger |
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License | BSD-3-Clause |
Published | |
Homepage | https://github.com/UnixJunkie/svmwrap |
Issue Tracker | https://github.com/UnixJunkie/svmwrap/issues |
Maintainer | unixjunkie@sdf.org |
Dependencies |
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Optional dependencies | |
Source [http] | https://github.com/UnixJunkie/svmwrap/archive/v3.1.0.tar.gz sha256=545f64d4bf17dade81969bc908f0951048e32030e16c5803971188373cabba8f md5=c9f2a1e633edc34a7c9499213298fe15 |
Edit | https://github.com/ocaml/opam-repository/tree/master/packages/svmwrap/svmwrap.3.1.0/opam |