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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 "dokeysto_camltc"
19]
20synopsis: "Wrapper around liblinear-tools"
21description: """
22Only L2-regularized logistic regression is supported currently.
23Each model is trained on balanced bootstraps from the training set
24(one bootstrap for the positive class, one for the negative class).
25The size of the bootstrap is the size of the smallest (under-represented)
26class. Bagging is supported and allows to obtain better models.
27
28usage: linwrap
29 -i <filename>: training set or DB to screen
30 [-o <filename>]: predictions output file
31 [-np <int>]: ncores
32 [-c <float>]: fix C
33 [-w <float>]: fix w1
34 [-k <int>]: number of bags for bagging (default=off)
35 [-n <int>]: folds of cross validation
36 [--seed <int>]: fix random seed
37 [-p <float>]: training set portion (in [0.0:1.0])
38 [{-l|--load} <filename>]: prod. mode; use trained models
39 [{-s|--save} <filename>]: train. mode; save trained models
40 [--scan-c]: scan for best C
41 [--scan-w]: scan weight to counter class imbalance
42 [--scan-k]: scan number of bags (advice: optim. k rather than w)
43"""
44url {
45 src: "https://github.com/UnixJunkie/linwrap/archive/v2.0.0.tar.gz"
46 checksum: [
47 "sha256=ff14f3f61e2cb92b6de9a9fae51dffab5226327c1ce18f0634cb9eed81bcd2f6"
48 "md5=ac460ea9915a488bc56d0acf9d966b04"
49 ]
50}