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micer  

Map Image Classification Efficacy
View on CRAN: Click here


Download and install micer package within the R console
Install from CRAN:
install.packages("micer")

Install from Github:
library("remotes")
install_github("cran/micer")

Install by package version:
library("remotes")
install_version("micer", "0.2.0")



Attach the package and use:
library("micer")
Maintained by
Aaron Maxwell
[Scholar Profile | Author Map]
First Published: 2025-01-20
Latest Update: 2025-01-20
Description:
Map image classification efficacy (MICE) adjusts the accuracy rate relative to a random classification baseline (Shao et al. (2021)<doi:10.1109/ACCESS.2021.3116526> and Tang et al. (2024)<doi:10.1109/TGRS.2024.3446950>). Only the proportions from the reference labels are considered, as opposed to the proportions from the reference and predictions, as is the case for the Kappa statistic. This package offers means to calculate MICE and adjusted versions of class-level user's accuracy (i.e., precision) and producer's accuracy (i.e., recall) and F1-scores. Class-level metrics are aggregated using macro-averaging. Functions are also made available to estimate confidence intervals using bootstrapping and statistically compare two classification results.
How to cite:
Aaron Maxwell (2025). micer: Map Image Classification Efficacy. R package version 0.2.0, https://cran.r-project.org/web/packages/micer. Accessed 21 Feb. 2025.
Previous versions and publish date:
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Complete documentation for micer
Functions, R codes and Examples using the micer R package
Full micer package functions and examples
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