Package: BiObjClass 0.1.0
BiObjClass: Classification of Algorithms
Implements the Bi-objective Lexicographical Classification method and Performance Assessment Ratio at 10% metric for algorithm classification. Constructs matrices representing algorithm performance under multiple criteria, facilitating decision-making in algorithm selection and evaluation. Analyzes and compares algorithm performance based on various metrics to identify the most suitable algorithms for specific tasks. This package includes methods for algorithm classification and evaluation, with examples provided in the documentation. Carvalho (2019) presents a statistical evaluation of algorithmic computational experimentation with infeasible solutions <doi:10.48550/arXiv.1902.00101>. Moreira and Carvalho (2023) analyze power in preprocessing methodologies for datasets with missing values <doi:10.1080/03610918.2023.2234683>.
Authors:
BiObjClass_0.1.0.tar.gz
BiObjClass_0.1.0.zip(r-4.5)BiObjClass_0.1.0.zip(r-4.4)BiObjClass_0.1.0.zip(r-4.3)
BiObjClass_0.1.0.tgz(r-4.4-any)BiObjClass_0.1.0.tgz(r-4.3-any)
BiObjClass_0.1.0.tar.gz(r-4.5-noble)BiObjClass_0.1.0.tar.gz(r-4.4-noble)
BiObjClass_0.1.0.tgz(r-4.4-emscripten)BiObjClass_0.1.0.tgz(r-4.3-emscripten)
BiObjClass.pdf |BiObjClass.html✨
BiObjClass/json (API)
# Install 'BiObjClass' in R: |
install.packages('BiObjClass', repos = c('https://tiagocsoares.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 months agofrom:d995b07108. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-win | OK | Oct 31 2024 |
R-4.5-linux | OK | Oct 31 2024 |
R-4.4-win | OK | Oct 31 2024 |
R-4.4-mac | OK | Oct 31 2024 |
R-4.3-win | OK | Oct 31 2024 |
R-4.3-mac | OK | Oct 31 2024 |
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
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Bilex Function | bilex |
par10 Function | par10 |