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Update package for CRAN compliance (0.4.0) (#11)
Brings the package back in line with current CRAN policies so it can be resubmitted after being unlisted. * Register native routines via R_registerRoutines (required since R 3.4) and disable dynamic symbol lookup. * Add FCONE / USE_FC_LEN_T for the F77_CALL(dgemv) call so it compiles against modern R headers. * Replace printf with Rprintf and drop stdio.h from C sources. * Replace T/F with TRUE/FALSE in R sources and tests. * print.ftrlprox now returns invisible(x) and documents @return. * DESCRIPTION: bump version to 0.4.0, drop unused LazyData, raise min R to 3.5.0, add stats to Imports, refresh RoxygenNote. * Documentation: fix ftrlprox.matrix -> ftrlprox.default reference, author typo, missing \value in print. * LICENSE: fix copyright holder spelling. * tests/testthat.R: pin RNGversion("3.5.0") so legacy hard-coded coefficient expectations remain reproducible after R 3.6's sample() change. * CI: drop .travis.yml in favour of r-lib/actions workflows for R-CMD-check (macOS/Windows/Ubuntu x release/devel/oldrel-1) and test-coverage. Refresh README badges.
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‎.Rbuildignore‎

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^.*\.Rproj$
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^\.Rproj\.user$
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^\.travis\.yml$
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^.*\.o$
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^Makefile$
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^\.github$
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^README\.md$
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^codecov\.yml$

‎.github/workflows/R-CMD-check.yaml‎

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# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
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on:
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push:
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branches: [main, master]
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pull_request:
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branches: [main, master]
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name: R-CMD-check
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jobs:
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R-CMD-check:
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runs-on: ${{ matrix.config.os }}
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name: ${{ matrix.config.os }} (${{ matrix.config.r }})
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strategy:
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fail-fast: false
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matrix:
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config:
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- {os: macos-latest, r: 'release'}
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- {os: windows-latest, r: 'release'}
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- {os: ubuntu-latest, r: 'devel', http-user-agent: 'release'}
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- {os: ubuntu-latest, r: 'release'}
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- {os: ubuntu-latest, r: 'oldrel-1'}
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env:
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GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
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R_KEEP_PKG_SOURCE: yes
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steps:
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- uses: actions/checkout@v4
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- uses: r-lib/actions/setup-pandoc@v2
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- uses: r-lib/actions/setup-r@v2
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with:
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r-version: ${{ matrix.config.r }}
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http-user-agent: ${{ matrix.config.http-user-agent }}
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use-public-rspm: true
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- uses: r-lib/actions/setup-r-dependencies@v2
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with:
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extra-packages: any::rcmdcheck
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needs: check
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- uses: r-lib/actions/check-r-package@v2
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with:
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upload-snapshots: true
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build_args: 'c("--no-manual","--compact-vignettes=gs+qpdf")'

‎.github/workflows/test-coverage.yaml‎

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# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
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on:
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push:
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branches: [main, master]
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pull_request:
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branches: [main, master]
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name: test-coverage
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jobs:
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test-coverage:
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runs-on: ubuntu-latest
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env:
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GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
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steps:
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- uses: actions/checkout@v4
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- uses: r-lib/actions/setup-r@v2
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with:
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use-public-rspm: true
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- uses: r-lib/actions/setup-r-dependencies@v2
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with:
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extra-packages: any::covr
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needs: coverage
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- name: Test coverage
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run: |
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covr::codecov(
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quiet = FALSE,
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clean = FALSE,
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install_path = file.path(normalizePath(Sys.getenv("RUNNER_TEMP"), winslash = "/"), "package")
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)
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shell: Rscript {0}
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- name: Show testthat output
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if: always()
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run: |
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## --------------------------------------------------------------------
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find ${{ runner.temp }}/package -name 'testthat.Rout*' -exec cat '{}' \; || true
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shell: bash
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- name: Upload test results
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if: failure()
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uses: actions/upload-artifact@v4
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with:
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name: coverage-test-failures
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path: ${{ runner.temp }}/package

‎.travis.yml‎

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‎DESCRIPTION‎

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Package: FTRLProximal
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Title: FTRL Proximal Implementation for Elastic Net Regression
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Version: 0.3.1
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Version: 0.4.0
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Authors@R: person("Vilhelm", "von Ehrenheim", email = "vonehrenheim@gmail.com", role = c("aut", "cre"))
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Description: Implementation of Follow The Regularized Leader (FTRL) Proximal algorithm, proposed by McMahan et al. (2013) <doi:10.1145/2487575.2488200>, used for online training of large scale regression models using a mixture of L1 and L2 regularization.
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Description: Implementation of Follow The Regularized Leader (FTRL) Proximal
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algorithm, proposed by McMahan et al. (2013)
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<doi:10.1145/2487575.2488200>, used for online training of large scale
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regression models using a mixture of L1 and L2 regularization.
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URL: https://github.com/while/FTRLProximal
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BugReports: https://github.com/while/FTRLProximal/issues
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Depends:
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R (>= 3.2.3)
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R (>= 3.5.0)
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Imports:
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Matrix,
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methods
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methods,
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stats
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License: MIT + file LICENSE
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Encoding: UTF-8
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LazyData: true
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RoxygenNote: 5.0.1
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Suggests:
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RoxygenNote: 7.3.2
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Suggests:
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testthat,
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covr,
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mlbench

‎LICENSE‎

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YEAR: 2016
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COPYRIGHT HOLDER: Vilhelm von Erenheim
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COPYRIGHT HOLDER: Vilhelm von Ehrenheim

‎NAMESPACE‎

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import(Matrix)
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importFrom(methods,as)
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importFrom(stats,model.matrix)
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useDynLib(FTRLProximal)
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useDynLib(FTRLProximal, .registration = TRUE)

‎R/ftrlprox.default.r‎

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#' @author Vilhelm von Ehrenheim
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#'
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#' @method ftrlprox default
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#' @useDynLib FTRLProximal
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#' @useDynLib FTRLProximal, .registration = TRUE
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#' @importFrom methods as
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#' @export
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##------------------------------------------------------------------------------
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ftrlprox.default <- function(x, y, lambda, alpha, a, b=1, num_epochs=1,
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save_loss=F, ...) {
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save_loss=FALSE, ...) {
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if (nrow(x) != length(y))
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stop(sprintf("Input has differing number of rows, nrow(x)=%d, length(y)=%d",
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nrow(x), length(y)))

‎R/ftrlprox.formula.r‎

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#' @param ... additional args
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#' @return ftrlprox model object
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#' @author Vilhelm von Ehrenheim
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#' @useDynLib FTRLProximal
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#' @useDynLib FTRLProximal, .registration = TRUE
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#' @importFrom stats model.matrix
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#' @export
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#'
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#' a = 0.3, lambda = 5.0, alpha = 1.0)
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#' print(mdl)
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##------------------------------------------------------------------------------
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ftrlprox.formula <- function(formula, data, lambda, alpha, a, b=1, num_epochs=1, save_loss=F, ...) {
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ftrlprox.formula <- function(formula, data, lambda, alpha, a, b=1, num_epochs=1, save_loss=FALSE, ...) {
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X <- model.matrix(formula, data)
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y <- data[[all.vars(formula[[2]])]]

‎R/ftrlprox.r‎

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#'
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#' Online elastic net regression using the FTRL Proximal algorithm for training.
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#'
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#' This is the generic method. Please look at ftrlprox.matrix and ftrlprox.formula for the model matrix and formula versions respectively.
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#' This is the generic method. Please look at ftrlprox.default and ftrlprox.formula for the model matrix and formula versions respectively.
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#'
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#' @param x the model matrix containing features
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#' @param ... the rest of the model parameters
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#' @return ftrlprox model object
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#' @author Vilhelm von Ehrenheim
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#'
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#' @useDynLib FTRLProximal
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#' @useDynLib FTRLProximal, .registration = TRUE
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#' @export
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##------------------------------------------------------------------------------
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ftrlprox <- function(x, ...) {

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