Package: rocTree 1.1.1

rocTree: Receiver Operating Characteristic (ROC)-Guided Classification and Survival Tree

Receiver Operating Characteristic (ROC)-guided survival trees and ensemble algorithms are implemented, providing a unified framework for tree-structured analysis with censored survival outcomes. A time-invariant partition scheme on the survivor population was considered to incorporate time-dependent covariates. Motivated by ideas of randomized tests, generalized time-dependent ROC curves were used to evaluate the performance of survival trees and establish the optimality of the target hazard/survival function. The optimality of the target hazard function motivates us to use a weighted average of the time-dependent area under the curve (AUC) on a set of time points to evaluate the prediction performance of survival trees and to guide splitting and pruning. A detailed description of the implemented methods can be found in Sun et al. (2019) <arxiv:1809.05627>.

Authors:Yifei Sun [aut], Mei-Cheng Wang [aut], Sy Han Chiou [aut, cre]

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rocTree.pdf |rocTree.html
rocTree/json (API)
NEWS

# Install 'rocTree' in R:
install.packages('rocTree', repos = c('https://stc04003.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/stc04003/roctree/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • simDat - Simulated dataset for demonstration

On CRAN:

decision-trees

3.40 score 5 stars 7 scripts 157 downloads 5 exports 91 dependencies

Last updated 4 years agofrom:56c9818858. Checks:OK: 1 NOTE: 5 WARNING: 3. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-win-x86_64WARNINGNov 21 2024
R-4.5-linux-x86_64NOTENov 21 2024
R-4.4-win-x86_64WARNINGNov 21 2024
R-4.4-mac-x86_64NOTENov 21 2024
R-4.4-mac-aarch64NOTENov 21 2024
R-4.3-win-x86_64WARNINGNov 21 2024
R-4.3-mac-x86_64NOTENov 21 2024
R-4.3-mac-aarch64NOTENov 21 2024

Exports:rocTreesimuSurvtrueHaztrueSurv

Dependencies:assertthatbase64encbbmlebdsmatrixBHbitbit64bslibcachemclicliprcolorspacecpp11crayondata.tabledata.treedeSolveDiagrammeRdigestdplyrevaluatefansifarverfastGHQuadfastmapflexsurvfontawesomefsgenericsggplot2gluegtablehighrhmshtmltoolshtmlwidgetsigraphisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemstatemuhazmunsellmvtnormnlmenumDerivpillarpkgconfigprettyunitsprogresspurrrquadprogR6rappdirsRColorBrewerRcppRcppArmadilloreadrrlangrmarkdownrstpm2rstudioapisassscalesstatmodstringistringrsurvivaltibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml