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Comparison · Analytics
ggspatial vs mlr3fselect
A side-by-side editorial comparison of ggspatial and mlr3fselect — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-stats
ggspatial vs mlr3fselect: at a glance
What is ggspatial?
ggspatial finishes its move off raster and onto terra
ggspatial puts spatial data into ggplot2. Its recent history is a single multi-year migration: terra support arrived alongside raster in 1.1.6, and by 1.1.10 terra is the default in the bundled data loaders while raster is described as deprecated. Everything between those two releases is ggplot2 compatibility patching.
What is mlr3fselect?
mlr3fselect turned feature selection into an asynchronous, distributable job
mlr3fselect runs feature selection for mlr3. The defining change in this window is 1.4.0, which introduced FSelectorAsync and the asynchronous instance classes, letting searches run without a synchronous batch loop. Around it sit ensemble feature selection work — fastVoteR ranking, embedded ensemble selection, result combination — and performance work on objective evaluation.
ggspatial vs mlr3fselect: editorial side-by-side
ggspatial
0.0ANALYTICS
ggspatial finishes its move off raster and onto terra
◆ Current state
ggspatial puts spatial data into ggplot2. Its recent history is a single multi-year migration: terra support arrived alongside raster in 1.1.6, and by 1.1.10 terra is the default in the bundled data loaders while raster is described as deprecated. Everything between those two releases is ggplot2 compatibility patching.
◆ Where it's heading
The package tracks the R spatial stack's own generational shift rather than setting direction itself — sf and stars support, then terra, then preparing S3 methods for the next ggplot2. Feature work is rare; the value it delivers is staying current with the layers underneath it.
◆ Prediction
The likely next step is completing the ggplot2 S3 method preparation that 1.1.10 started, with raster support eventually dropped rather than maintained in parallel.
mlr3fselect
0.0ANALYTICS
mlr3fselect turned feature selection into an asynchronous, distributable job
◆ Current state
mlr3fselect runs feature selection for mlr3. The defining change in this window is 1.4.0, which introduced FSelectorAsync and the asynchronous instance classes, letting searches run without a synchronous batch loop. Around it sit ensemble feature selection work — fastVoteR ranking, embedded ensemble selection, result combination — and performance work on objective evaluation.
◆ Where it's heading
Two threads run in parallel: scaling the search itself through async execution and the rush backend, and making ensemble selection results easier to analyse via Pareto fronts, knee points and now removal of empty result rows. The rush backward-compatibility shim was dropped in 1.6.0, so the async path is now the assumed one.
◆ Prediction
Expect the ensemble result API to keep gaining analysis helpers, with async execution treated as the default rather than an option.
Alternatives to ggspatial and mlr3fselect
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either ggspatial or mlr3fselect.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all ggspatial alternatives → · See all mlr3fselect alternatives →
Recent activity from ggspatial and mlr3fselect
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agomlr3fselectEmpty-selection rows removable from ensemble results
- 8mo agomlr3fselectFaster objective evaluation and always_included roles
- 11mo agoggspatialterra becomes the default raster backend
- 1y agomlr3fselectAsynchronous feature selection arrives with FSelectorAsync ⚡
- 1y agomlr3fselectEmbedded ensemble selection and result combination
- 1y agomlr3fselectInternal tuning callback added
- 1y agomlr3fselectmlr3 0.21.0 compatibility and archive slimming
- 2y agoggspatialExample fixes for the updated raster/terra stack
- 3y agoggspatialannotation_spatial() fix for the latest ggplot2
- 3y agoggspatialFix for behaviour deprecated in ggplot2
- 3y agoggspatialterra support, categorical rasters and better stars handling
- 8y agoggspatialPackage size and CRAN check time reduced
Frequently asked questions
What is the difference between ggspatial and mlr3fselect?
Both compete on the same themes — r-stats — within Analytics. ggspatial and mlr3fselect are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is ggspatial better than mlr3fselect?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggspatial and mlr3fselect are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to ggspatial?
Top ggspatial alternatives in Analytics are ranked by recent ship velocity. Browse the "ggspatial alternatives" section above for the current picks, or visit /alternatives/ggspatial for the full list with editorial commentary on each.
What are the best alternatives to mlr3fselect?
Top mlr3fselect alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3fselect alternatives" section above for the current picks, or visit /alternatives/mlr3fselect for the full list with editorial commentary on each.