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 caiohamamura@gmail.com (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
Imports
Useful links:
Report bugs at https://github.com/caiohamamura/tabularMLC/issues
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