tabularMLC-package: Tabular maximum likelihood classifier

Description Details Author(s) References See Also


Maximum likelihood is a common classifier used for land use classification. It calculates the likelihood of an object to belong to each class based on an expected distribution and a metric of distance.


The most common implementation, like in this package, will assume normal distributed variables within classes, and calculate the distance, based on Mahalanobis distance.


Maintainer: Caio Hamamura (ORCID)


Mather, P. M. (1985). Remote sensing letters: A computationally efficient maximum-likelihood classifier employing prior probabilities for remotely-sensed data. International Journal of Remote Sensing, 6(2), 369–376. doi: 10.1080/01431168508948456


See Also

Useful links:

tabularMLC documentation built on Oct. 5, 2021, 9:07 a.m.