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rasclass
View on CRAN: Click
here
Download and install rasclass package within the R console
Install from CRAN:
install.packages("rasclass")
Install from Github:
library("remotes")
install_github("cran/rasclass")
Install by package version:
library("remotes")
install_version("rasclass", "0.2.2")
Attach the package and use:
library("rasclass")
Maintained by
Daniel Wiesmann
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.rasclass . rasclass results . rasclass.pdf . rasclass_0.2.2.tar.gz . rasclass_0.2.2.zip . rasclass_0.2.2.zip . rasclass_0.2.2.zip . rasclass_0.2.2.tgz . rasclass_0.2.2.tgz . rasclass_0.2.2.tgz . rasclass_0.2.2.tgz . rasclass_0.2.2.tgz . rasclass_0.2.2.tgz . rasclass archive . https://CRAN.R-project.org/package=rasclass .
First Published: 2011-08-22
Latest Update: 2016-05-02
Description:
Software to perform supervised and pixel based raster image classification. It has been designed to facilitate land-cover analysis. Five classification algorithms can be used: Maximum Likelihood Classification, Multinomial Logistic Regression, Neural Networks, Random Forests and Support Vector Machines. The output includes the classified raster and standard classification accuracy assessment such as the accuracy matrix, the overall accuracy and the kappa coefficient. An option for in-sample verification is available.
How to cite:
Daniel Wiesmann (2011). rasclass: Supervised Raster Image Classification. R package version 0.2.2, https://cran.r-project.org/web/packages/rasclass. Accessed 26 Mar. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for rasclass
Functions, R codes and Examples using
the rasclass R package
Some associated functions: buildFormula . checkRasclass . classifyRasclass . rasclass-class . rasclass-package . rasclassMlc . rasclassRaster-class . readRaster . readRasterFolder . setRasclassData . writeRaster .
Some associated R codes: 1_setClasses.R . buildFormula.R . checkRasclass.R . classifyRasclass.R . rasclassMlc.R . readRaster.R . readRasterFolder.R . serviceFunctions.R . setRasclassData.R . writeRaster.R . Full rasclass package functions and examples
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