Science Score: 13.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○Academic publication links
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○Scientific vocabulary similarity
Low similarity (12.1%) to scientific vocabulary
Last synced: 9 months ago
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JSON representation
Repository
Basic Info
- Host: GitHub
- Owner: maxwell-geospatial
- License: gpl-3.0
- Language: R
- Default Branch: main
- Size: 21.5 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 1 year ago
· Last pushed over 1 year ago
Metadata Files
Readme
License
README.Rmd
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# micer
# geodl 
## Installation
You can install the development version of micer from [GitHub](https://github.com/) with:
```r
# install.packages("devtools")
devtools::install_github("maxwell-geospatial/micer")
```
## Intro to micer
The goal of this simple R package is to allow for the calculation of map image classification efficacy (MICE) and associated metrics. MICE was originally proposed in the following paper:
Shao, G., Tang, L. and Zhang, H., 2021. Introducing image classification efficacies. *IEEE Access*, 9, pp.134809-134816.
It was further explored in the following paper:
Tang, L., Shao, J., Pang, S., Wang, Y., Maxwell, A., Hu, X., Gao, Z., Lan, T. and Shao, G., 2024. Bolstering Performance Evaluation of Image Segmentation Models with Efficacy Metrics in the Absence of a Gold Standard. *IEEE Transactions on Geoscience and Remote Sensing*.
MICE is an alternative accuracy assessment. It adjusts the accuracy rate relative to a random classification baseline. 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 specifically calculates MICE and adjusted versions of class-level user's (i.e., precision) and producer's (i.e., recall) accuracies and F1-scores. Class-level metrics are aggregated using macro-averaging in which each class contributes equally. Functions are also made available to estimate confidence intervals using bootstrapping and to statistically compare two classification results.
Owner
- Login: maxwell-geospatial
- Kind: user
- Repositories: 7
- Profile: https://github.com/maxwell-geospatial
GitHub Events
Total
- Push event: 4
- Create event: 2
Last Year
- Push event: 4
- Create event: 2
Packages
- Total packages: 1
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Total downloads:
- cran 166 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 1
- Total maintainers: 1
cran.r-project.org: micer
Map Image Classification Efficacy
- Homepage: https://github.com/maxwell-geospatial/micer
- Documentation: http://cran.r-project.org/web/packages/micer/micer.pdf
- License: GPL (≥ 3)
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Latest release: 0.2.0
published over 1 year ago
Rankings
Dependent packages count: 27.4%
Dependent repos count: 33.8%
Average: 49.4%
Downloads: 86.9%
Maintainers (1)
Last synced:
10 months ago
Dependencies
DESCRIPTION
cran
- R >= 2.10 depends
- dplyr >= 1.1.3 imports
- knitr * suggests
- rmarkdown * suggests