Tabular Maximum Likelihood Classifier
Overview
The maximum likelihood classifier (MLC) is one of the most common classifiers used for remote sensing imagery. This package uses 'RcppArmadillo' to provide a fast implementation of the MLC to train and predict over tabular data (data.frame). The algorithms were based on Mather (1985) doi:10.1080/01431168508948456 method.
- Use methods::is for checking classes
- Remove force compilation flag CXX_STD = CXX11
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-08
- NOTE12 OK, 1 NOTE2026-06-07
- OK14 OK2026-04-22
Show 2 earlier changesHide 2 earlier changes
- ERROR13 OK, 1 ERROR2026-04-18
- OK14 OK2026-03-10
Documentation
- Help pages
- 4includes a package overview page
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 25%
Downloads
Repository
Stars over time
Releases over time
6 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/caiohamamura/tabularmlc on 2026-10-22.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
Dependencies
Installing tabularMLC adds 2 packages (2 with compiled code, 2.8 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 0.0.4Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 0.0.32021-10-05
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-10-05
- Total releases
- 2 / 5 yrs
- License
- GPL-3 OSI
- Download size
- 7.2 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("tabularMLC")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.