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anil.recoil.org
1opam-version: "2.0"
2authors: "Francois Berenger"
3maintainer: "unixjunkie@sdf.org"
4homepage: "https://github.com/UnixJunkie/linwrap"
5bug-reports: "https://github.com/UnixJunkie/linwrap/issues"
6dev-repo: "git+https://github.com/UnixJunkie/linwrap.git"
7license: "BSD-3-Clause"
8build: ["dune" "build" "-p" name "-j" jobs]
9depends: [
10 "base-unix"
11 "batteries"
12 "cpm"
13 "dolog" {>= "4.0.0" & < "5.0.0"}
14 "dune" {>= "1.10"}
15 "minicli"
16 "parany" {>= "6.0.0" & < "10.0.0"}
17 "conf-liblinear-tools"
18]
19synopsis: "Wrapper around liblinear-tools"
20description: """
21Only L2-regularized logistic regression is supported currently.
22Each model is trained on balanced bootstraps from the training set
23(one bootstrap for the positive class, one for the negative class).
24The size of the bootstrap is the size of the smallest (under-represented)
25class. Bagging is supported and allows to obtain better models.
26
27usage: linwrap
28 -i <filename>: training set or DB to screen
29 [-o <filename>]: predictions output file
30 [-np <int>]: ncores
31 [-c <float>]: fix C
32 [-w <float>]: fix w1
33 [-k <int>]: number of bags for bagging (default=off)
34 [-n <int>]: folds of cross validation
35 [--seed <int>]: fix random seed
36 [-p <float>]: training set portion (in [0.0:1.0])
37 [{-l|--load} <filename>]: prod. mode; use trained models
38 [{-s|--save} <filename>]: train. mode; save trained models
39 [--scan-c]: scan for best C
40 [--scan-w]: scan weight to counter class imbalance
41 [--scan-k]: scan number of bags (advice: optim. k rather than w)
42"""
43url {
44 src: "https://github.com/UnixJunkie/linwrap/archive/v0.0.1.tar.gz"
45 checksum: [
46 "sha256=460bbd11012e1d081497a03a42737562aa3333f0ec7913d4aea601ad866afb9f"
47 "md5=4456917240f47526a681d1230d53ebf8"
48 ]
49}