Package: OTE 1.0.1
Zardad Khan
OTE: Optimal Trees Ensembles for Regression, Classification and Class Membership Probability Estimation
Functions for creating ensembles of optimal trees for regression, classification (Khan, Z., Gul, A., Perperoglou, A., Miftahuddin, M., Mahmoud, O., Adler, W., & Lausen, B. (2019). (2019) <doi:10.1007/s11634-019-00364-9>) and class membership probability estimation (Khan, Z, Gul, A, Mahmoud, O, Miftahuddin, M, Perperoglou, A, Adler, W & Lausen, B (2016) <doi:10.1007/978-3-319-25226-1_34>) are given. A few trees are selected from an initial set of trees grown by random forest for the ensemble on the basis of their individual and collective performance. Three different methods of tree selection for the case of classification are given. The prediction functions return estimates of the test responses and their class membership probabilities. Unexplained variations, error rates, confusion matrix, Brier scores, etc. are also returned for the test data.
Authors:
OTE_1.0.1.tar.gz
OTE_1.0.1.tar.gz(r-4.5-noble)OTE_1.0.1.tar.gz(r-4.4-noble)
OTE_1.0.1.tgz(r-4.4-emscripten)OTE_1.0.1.tgz(r-4.3-emscripten)
OTE.pdf |OTE.html✨
OTE/json (API)
# Install 'OTE' in R: |
install.packages('OTE', repos = c('https://cran.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 5 years agofrom:9563536199. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 10 2024 |
R-4.5-linux | OK | Dec 10 2024 |
Exports:OTClassOTProbOTRegPredict.OTClassPredict.OTProbPredict.OTReg
Dependencies:randomForest