opam-version: "2.0"
authors: "Francois Berenger"
maintainer: "unixjunkie@sdf.org"
homepage: "https://github.com/UnixJunkie/svmwrap"
bug-reports: "https://github.com/UnixJunkie/svmwrap/issues"
dev-repo: "git+https://github.com/UnixJunkie/svmwrap.git"
license: "BSD-3-Clause"
build: ["dune" "build" "-p" name "-j" jobs]
depends: [
  "base-unix"
  "batteries"
  "conf-libsvm-tools"
  "cpm" {>= "11.0.0"}
  "dolog" {>= "6.0.0"}
  "dune" {>= "2.9"}
  "minicli" {>= "5.0.0"}
  "molenc" {>= "16.0.0"}
  "parany" {>= "11.0.0"}
  "line_oriented" {>= "1.2.0"}
  "nlopt-ocaml" {>= "0.5.1"}
]
# the software can compile and install without the depopts.
# however, some tools and options will not work anymore at run-time
depopts: [
  "conf-gnuplot"
]
synopsis: "Wrapper on top of libsvm-tools"
description: """
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
  [-o <filename>]: predictions output file
  [-np <int>]: ncores
  [--kernel <string>] choose kernel type {Lin|RBF|Sig|Pol}
  [-c <float>]: fix C
  [-e <float>]: epsilon in the loss function of epsilon-SVR;
  (0 <= epsilon <= max_i(|y_i|))
  [--nlopt <int>]: use NLopt with MAX_ITER (global optim.)
  instead of grid-search (recommended: MAX_ITER >= 100)
  [-g <float>]: fix gamma (for RBF and Sig kernels)
  [-r <float>]: fix r for the Sig kernel
  [--iwn]: turn ON instance-wise-normalization
  [--scale]: turn ON [0:1] scaling (NOT PRODUCTION READY)
  [--no-plot]: no gnuplot
  [{-n|--NxCV} <int>]: folds of cross validation
  [-q]: quiet
  [-v|--verbose]: equivalent to not specifying -q
  [--seed <int>]: fix random seed
  [-p <float>]: training set portion (in [0.0:1.0])
  [--pairs]: read from .AP files (atom pairs; will offset feat. indexes by 1)
  [--train <train.liblin>]: training set (overrides -p)
  [--valid <valid.liblin>]: validation set (overrides -p)
  [--test <test.liblin>]: test set (overrides -p)
  [{-l|--load} <filename>]: prod. mode; use trained models
  [{-s|--save} <filename>]: train. mode; save trained models
  [-f]: force overwriting existing model file
  [--scan-c]: scan for best C
  [--scan-e <int>]: epsilon scan #steps for SVR
  [--scan-g]: scan for best gamma
  [--regr]: regression (SVR); also, implied by -e and --scan-e
  [--e-range <float>:<int>:<float>]: specific 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')
"""
url {
  src: "https://github.com/UnixJunkie/svmwrap/archive/v4.0.0.tar.gz"
  checksum: [
    "sha256=0904f363cd48ffc16f670e0d0a6b7bc45992a463daff7ef1443b65e9980dc6e6"
    "md5=faa68465c3574c9e1550e9c7bb1b7234"
  ]
}