Package: Iscores 1.1.0
Iscores: Proper Scoring Rules for Missing Value Imputation
Implementation of a KL-based scoring rule to assess the quality of different missing value imputations in the broad sense as introduced in Michel et al. (2021) <arxiv:2106.03742>.
Authors:
Iscores_1.1.0.tar.gz
Iscores_1.1.0.zip(r-4.5)Iscores_1.1.0.zip(r-4.4)Iscores_1.1.0.zip(r-4.3)
Iscores_1.1.0.tgz(r-4.4-any)Iscores_1.1.0.tgz(r-4.3-any)
Iscores_1.1.0.tar.gz(r-4.5-noble)Iscores_1.1.0.tar.gz(r-4.4-noble)
Iscores_1.1.0.tgz(r-4.4-emscripten)Iscores_1.1.0.tgz(r-4.3-emscripten)
Iscores.pdf |Iscores.html✨
Iscores/json (API)
# Install 'Iscores' in R: |
install.packages('Iscores', repos = c('https://missvalteam.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/missvalteam/iscores/issues
imputation-methodsmachine-learningmissing-valuesrandom-forest
Last updated 2 years agofrom:c4fb5184ec. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 13 2024 |
R-4.5-win | OK | Oct 13 2024 |
R-4.5-linux | OK | Oct 13 2024 |
R-4.4-win | OK | Oct 13 2024 |
R-4.4-mac | OK | Oct 13 2024 |
R-4.3-win | OK | Oct 13 2024 |
R-4.3-mac | OK | Oct 13 2024 |
Exports:Iscores
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Balancing of Classes | class.balancing |
Combining projection forests | combine2Forests |
Combining a list of forest | combineForests |
compute the density ratio score | compute_drScore |
Computation of the density ratio score | densityRatioScore |
doevaluation: compute the imputation KL-based scoring rules | doevaluation |
Iscores: compute the imputation KL-based scoring rules | Iscores |
Sampling of Projections | sample.vars.proj |
Truncation of probability | truncProb |