R Observatory: Metrics for sense version 1.2.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

sense

1.2.0Package record

Automatic Stacked Ensemble for Regression Tasks

0packages depend

2.9Kdownloads / year

89.9%test coverage

13/13flavors OK

Overview

About

Maintained by Giancarlo VercellinoCRAN page ↗Website ↗

Stacked ensembles for regression tasks using the 'mlr3' framework, internal preprocessing and out-of-fold stacking, and hyperparameter tuning using grid or random search. Supports numeric and categorical predictors.

Changes in 1.2.0

Replaced all mlr3pipelines graph and PipeOp usage with an internal mlr3 regression learner providing fitted preprocessing, three-fold out-of-fold stacking, optional base-learner selection, and averaging or learned stacking. The package no longer needs mlr3pipelines to install, load, train or predict.
Removed the mlr3viz, visNetwork, tictoc, forcats, readr, lubridate, purrr and Metrics dependencies. Mapping, timing, regression metrics, categorical processing and pipeline diagrams now use internal/base R code. R6 is now declared directly for the internal mlr3 learner.
Moved mlr3filters to Suggests; correlation and variance are internal. Specialized filters still use their original optional backends, preserving their algorithms. Removed unused direct suggestions of mlr3misc and nloptr.
Preserved the sense() arguments and result element names. plot is now a sense_pipeline object, drawn with plot(result$plot), rather than an HTML widget. time_log is a base R difftime. java_mem is accepted but unused. Stored model internals no longer have the GraphLearner/PipeOp layout.

Show all changes in 1.2.0Hide the rest of the changes in 1.2.0

Fixed deployment predictions to use a model refitted on all supplied rows, independently of outer evaluation. Fit preprocessing and feature selection inside every stacking fold; perform benchmarking inside each ensemble fit rather than selecting algorithms using the full data before outer evaluation. Benchmark scores are now out-of-fold scores and respect the measure's direction.
Added handling for unseen categories, constant/all-missing numeric columns, stable prediction schemas, finite input validation and reproducible fitting without changing the caller's random state or Java options.
Bound nearest-neighbour tuning by the smallest training split, avoid invalid zero SVM nu/eta candidates, and let ranger choose mtry for each encoded schema. Random search is capped by both budget and n_evals; one-candidate batches prevent overshooting the evaluation cap. Time limits are checked between trials.
Added base R regression and integration tests and a runnable migration vignette describing the architecture, optional dependencies and compatibility changes.
Converted the migration vignette from PDF/LaTeX (.Rnw) to a knitr HTML vignette (.Rhtml), so building and checking the package no longer requires a LaTeX installation or Ghostscript.

From NEWS.md in the release

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("sense", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-sense

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-sense

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-sense

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 2.4 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-09-12
NOTE12 OK, 2 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.2.0

READMENoVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 1.2.0Citation fileNoWebsiteYes

Help pages: 3includes a package overview page
Examples that run: 0%1 never run
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 0%

Vignettes (1)

Regression ensembles without mlr3pipelines

How these are measured

Downloads

2.9K

CRAN downloads in the past year

Rank #11,502 · ~8/day · ~246/mo

Releases R versions

Daily download trend is not available in this view yet.

42030 days

94290 days

2.9K1 year

Compare downloads with other packages →

Also on82 r2u3 autocran

How downloads are counted

Dependencies

Declared dependencies

19 external dependencies (excludes base and recommended)

Installing sense adds 31 packages (16 with compiled code, 20 MB of source tarballs). Heaviest: data.table 5.7 MB, palmerpenguins 2.9 MB, moocore 1.9 MB.

Depends (1)

R >= 4.1

Imports (10)

mlr3 mlr3learners paradox mlr3tuning bbotk data.table (>= 1.14.0)R6statsgraphicsutils

LinkingTo (0)

none

Suggests (13)

testthat mlr3filters knitr xgboostrpartranger kknn (>= 1.3.1)glmnet e1071 FSelectorRcpp (>= 0.3.8)care praznik lme4 (>= 1.1-27.1)

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (1)

Giancarlo Vercellino

Author, Maintainer since 1.0.0 (2021)

Releases (3)

Pick two releases to compare their code metrics.

1.2.0Latest
record
2026-09-08 · current release · diff ↗
R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
1.1.0
record
2024-06-19 · diff ↗
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
1.0.0
record
2021-09-06
R
R 4.1.0 released · 2021-05-18

Package metadata

First published: 2021-09-06
Total releases: 3 / 5 yrs
License: GPL-3 OSI
Minimum R: ≥ 4.1
Bundled data: 9.0 KB / 1 file
Download size: 33 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("sense")

Format

Vercellino, G. (2026). sense: Automatic Stacked Ensemble for Regression Tasks (Version 1.2.0) [Computer software]. https://doi.org/10.32614/CRAN.package.sense

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for sense version 1.2.0 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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