Installation and Loading | Installation | Load Package | High Dimensional Regression | Runtime of autotune Lasso | Comparison with Lasso tuned via Cross Validation (CV Lasso) | Runtime of CV Lasso | Comparison of quality of tuning between autotune and CV Lasso | Comparison on real data provided in Scaled Lasso's R package scalreg | Comparing prediction errors of autotune and benchmarks: CV and Scaled Lasso | Comparing via bootstrap
Package: autotune 0.1.0
autotune: Faster and more Efficient Lasso (than 'glmnet' and 'scalreg') with Data-Driven Tuning
Fits Lasso paths for high-dimensional regression using coordinate descent with automatic, data-driven tuning of the regularization parameter. The implementation is 10 to 50 times faster than the standard 'glmnet' implementation of Lasso and over 100 times faster than scaled Lasso. It also provides a reliable estimate of the regression noise level.
Authors:
autotune_0.1.0.tar.gz
autotune_0.1.0.zip(r-4.7-x86_64)autotune_0.1.0.zip(r-4.7-arm64)autotune_0.1.0.zip(r-4.6-x86_64)autotune_0.1.0.zip(r-4.6-arm64)autotune_0.1.0.zip(r-4.5-x86_64)
autotune_0.1.0.tgz(r-4.6-x86_64)autotune_0.1.0.tgz(r-4.6-arm64)autotune_0.1.0.tgz(r-4.5-x86_64)autotune_0.1.0.tgz(r-4.5-arm64)
autotune_0.1.0.tar.gz(r-4.7-arm64)autotune_0.1.0.tar.gz(r-4.7-x86_64)autotune_0.1.0.tar.gz(r-4.6-arm64)autotune_0.1.0.tar.gz(r-4.6-x86_64)
autotune_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
autotune/json (API)
| # Install 'autotune' in R: |
| install.packages('autotune', repos = c('https://tathagata-s.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tathagata-s/autotune/issues
Datasets:
- sp500 - S&P 500 Stock Data
Last updated from:9d4d570df5. Checks:15 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 165 | ||
| linux-devel-x86_64 | OK | 143 | ||
| source / vignettes | OK | 218 | ||
| linux-release-arm64 | OK | 154 | ||
| linux-release-x86_64 | OK | 180 | ||
| macos-release-arm64 | OK | 192 | ||
| macos-release-x86_64 | OK | 293 | ||
| macos-oldrel-arm64 | OK | 183 | ||
| macos-oldrel-x86_64 | OK | 505 | ||
| windows-devel-arm64 | OK | 325 | ||
| windows-devel-x86_64 | OK | 149 | ||
| windows-release-arm64 | OK | 314 | ||
| windows-release-x86_64 | OK | 100 | ||
| windows-oldrel-x86_64 | OK | 100 | ||
| wasm-release | OK | 143 |
Exports:autotune_lasso
Dependencies:Rcpp
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| autotune: Lasso with data-driven tuning for linear models | autotune-package autotune |
| Data-adaptive automatic and fast tuning of LM with Lasso regularization | autotune_lasso |
| Extract coefficients for autotune_lasso objects | coef.autotune_lasso coef.autotune_lasso_path |
| Plots for autotune_lasso objects | plot.autotune_lasso |
| Predict from a autotune_lasso fit | predict.autotune_lasso |
| S&P 500 Stock Data | sp500 |