OTE
1.0.1Optimal Trees Ensembles for Regression, Classification and Class Membership Probability Estimation
Overview
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.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
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- Return-value docs
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- References docs
- 89%
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2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 1.0.1Latest
- unarchivedReturned to CRAN2020-04-20
- archivedRemoved from CRAN2020-03-29check problems were not corrected in time
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- 1.02015-07-31
- RR 3.2.0 released · 2015-04-16
Package metadata
- First published
- 2015-07-31
- Total releases
- 2 / 11 yrs
- License
- GPL (>= 3) OSI
- Bundled data
- 29 KB / 2 files
- Download size
- 37 KB
- Installed size
- not tracked yet
- With dependencies
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