Package: nerfplus 1.0.0
nerfplus: Network-Assisted Random Forest+ (NeRF+)
Network-assisted Random Forest+ (NeRF+) is a flexible and interpretable machine learning model for incorporating network data alongside node-level covariate information. Briefly, NeRF+ extends a generalization of random forests (RF) called RF+ to the network-assisted regression setting by incorporating both a network cohesion penalty and network embeddings as additional covariates. Using this approach, NeRF+ inherits both the flexibility and interpretability of RFs while allowing researchers to easily incorporate network information in their model to further improve predictive performance. This package provides tools to fit and interpret NeRF+ models, as detailed in Tang, Levina, and Zhu (2025) <doi:10.48550/arXiv.2509.15611>.
Authors:
nerfplus_1.0.0.tar.gz
nerfplus_1.0.0.zip(r-4.7-x86_64)nerfplus_1.0.0.zip(r-4.7-arm64)nerfplus_1.0.0.zip(r-4.6-x86_64)nerfplus_1.0.0.zip(r-4.6-arm64)
nerfplus_1.0.0.tar.gz(r-4.7-arm64)nerfplus_1.0.0.tar.gz(r-4.7-x86_64)nerfplus_1.0.0.tar.gz(r-4.6-arm64)nerfplus_1.0.0.tar.gz(r-4.6-x86_64)
nerfplus_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
nerfplus/json (API)
| # Install 'nerfplus' in R: |
| install.packages('nerfplus', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tiffanymtang/nerfplus/issues
Pkgdown/docs site:https://tiffanymtang.github.io
- example_data - Example dataset for NeRF+ demonstration
Last updated from:2648ed6bf3. Checks:10 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 191 | ||
| linux-devel-x86_64 | OK | 230 | ||
| source / vignettes | OK | 291 | ||
| linux-release-arm64 | OK | 181 | ||
| linux-release-x86_64 | OK | 283 | ||
| windows-devel-arm64 | OK | 288 | ||
| windows-devel-x86_64 | OK | 253 | ||
| windows-release-arm64 | OK | 320 | ||
| windows-release-x86_64 | OK | 221 | ||
| wasm-release | OK | 168 |
Exports:fit_network_embeddingget_feature_importancesget_loointerpret_nerfplusnerfplusnerfplus_conformalnerfplus_cvoos_network_embeddingrncrnc_cvrun_app
Dependencies:abindcaretclasscliclockcodetoolscpp11data.tablediagramdplyre1071farverforeachfurrrfuturefuture.applygenericsggplot2glmnetglobalsgluegowergtablehardhatipredirlbaisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixModelMetricsnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6rangerRColorBrewerRcppRcppArmadilloRcppEigenrecipesreshape2rlangrpartS7scalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithryardstick
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Example dataset for NeRF+ demonstration | example_data |
| Wrapper to fit various network embedding methods | fit_network_embedding |
| Compute feature importances for a NeRF+ model | get_feature_importances |
| Compute Leave-One-Out (LOO) predictions and parameter changes for a NeRF+ model | get_loo |
| Interpret NeRF+ Model | interpret_nerfplus |
| Fit Network-assisted Random Forest+ (NeRF+) | nerfplus |
| Conformal prediction method for NeRF+ | nerfplus_conformal |
| Fit Network-assisted Random Forest+ (NeRF+) with Cross-Validation | nerfplus_cv |
| Out-of-sample network embedding method | oos_network_embedding |
| Predict method for a NeRF+ model | predict.nerfplus |
| Predict method for rnc (regression with network cohesion) objects | predict.rnc |
| Fit regression with network cohesion | rnc |
| Fit regression with network cohesion with cross-validation wrapper | rnc_cv |
| Run Shiny NeRF+ Interpret application | run_app |
