BSD Ports

math/R-cran-ranger 0.18.0 FreeBSD

Fast implementation of random forests

System
FreeBSD
Repository
FreeBSD ports
Maintainer
[email protected]
Port added
Last update
Commit
08983821d4
License
GPLv3
Categories
math

Description

A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Sparse matrices of class dgCMatrix can be analyzed directly.

Version history 1

  1. 0.18.0 08983821d4

Upstream's version as each commit to the port's Makefile set it, or as this site first saw it in the system's packages; the tree's own revisions are not versions here.

Install

Binary package:

pkg install R-cran-ranger

From the ports tree:

cd /usr/ports/math/R-cran-ranger/ && make install clean

To depend on this port in another port's Makefile:

RUN_DEPENDS=	R-cran-ranger>0:math/R-cran-ranger

Packages

The version each package repository carries. “-” means the repository builds no package of it, “n/a” that there is no such repository.

Repositoryaarch64amd64armv6armv7i386
FreeBSD:14:latest----0.18.0
FreeBSD:14:quarterly--n/a--
FreeBSD:15:latest-0.18.0n/a--
FreeBSD:15:quarterly--n/an/an/a
FreeBSD:16:latest-0.18.0n/an/an/a
FreeBSD:16:quarterlyn/an/an/an/an/a

Dependency graph

Ports that need it on the left, what it needs to run on the right; at most 8 of each. "Dependencies" below lists them all.

Dependencies

As this port's Makefile names them.

Runtime 2

Test 2

The full lists below include those, and their dependencies in turn.

Build dependencies 85
Run dependencies 87

No port depends on this one.

Configuration

No options to configure.

USES
cran:auto-plist,compiles
Service scripts
none

Files

distinfo 1
FileSizeSHA256
ranger_0.18.0.tar.gz17869594c5e4c67cd92292bbba72e71d1a89be6ddea1a0d7b8e7ad452e0609b675b44d

Commit history 1

DateCommitCreditsLog message
08983821d4 Christos Longros math/R-cran-ranger: New port: Fast implementation of random forests
Fast implementation of Random Forests for classification, regression, survival and probability prediction, suited for high dimensional data. Approved by: jrm (mentor) Differential Revision: https://reviews.freebsd.org/D61244