tabularMLC-package: Tabular maximum likelihood classifier
In tabularMLC: Tabular Maximum Likelihood Classifier
tabularMLC-package R Documentation
Tabular maximum likelihood classifier
Description
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.
Details
The most common implementation, like in this package, will assume normal
distributed variables within classes, and calculate the distance, based
on Mahalanobis distance.
Author(s)
Maintainer: Caio Hamamura caiohamamura@gmail.com (ORCID)
References
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.
\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/01431168508948456")}
Imports
See Also
Useful links:
tabularMLC documentation built on Nov. 5, 2025, 7:25 p.m.
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| tabularMLC-package | R Documentation |
Tabular maximum likelihood classifier
Description
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.
Details
The most common implementation, like in this package, will assume normal distributed variables within classes, and calculate the distance, based on Mahalanobis distance.
Author(s)
Maintainer: Caio Hamamura caiohamamura@gmail.com (ORCID)
References
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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/01431168508948456")}
Imports
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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