tidytext
Finished, widely taught, and shipping roxygen fixes.
Comparison · Analytics
ggspatial vs mlr3mbo
A side-by-side editorial comparison of ggspatial and mlr3mbo — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-stats
ggspatial vs mlr3mbo: 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 mlr3mbo?
mlr3mbo picked its defaults from a benchmark study, not from taste
mlr3mbo does model-based and Bayesian optimisation for mlr3. Its 1.0.0 release added a dictionary of pre-built acquisition-function optimisers and, more consequentially, replaced the default surrogate, acquisition function and optimiser settings with values derived from a large-scale benchmark study. The releases since are corrections to the acquisition-optimiser path exposed by that new default configuration.
ggspatial vs mlr3mbo: 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.
mlr3mbo
2.5ANALYTICS
mlr3mbo picked its defaults from a benchmark study, not from taste
◆ Current state
mlr3mbo does model-based and Bayesian optimisation for mlr3. Its 1.0.0 release added a dictionary of pre-built acquisition-function optimisers and, more consequentially, replaced the default surrogate, acquisition function and optimiser settings with values derived from a large-scale benchmark study. The releases since are corrections to the acquisition-optimiser path exposed by that new default configuration.
◆ Where it's heading
The package has moved from a toolkit that expected users to assemble a Bayesian optimisation loop into one with a defensible default loop, and the recent fixes — warm-start sizing on multi-objective archives, silently discarded terminators, stale x_domain values — are the consequences of more people running the default path.
◆ Prediction
Expect continued hardening of the acquisition-optimiser classes rather than new acquisition functions.
Alternatives to ggspatial and mlr3mbo
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 mlr3mbo.
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 mlr3mbo alternatives →
Recent activity from ggspatial and mlr3mbo
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 23d agomlr3mboAcquisition optimiser fixes for warm starts and archives
- 3mo agomlr3mboDictionary lookup and restart-limit fixes
- 4mo agomlr3mborush 1.0.0 compatibility and Surrogate$check()
- 5mo agomlr3mbomlr3mbo 1.0.0 ships benchmark-derived default settings ⚡
- 10mo agomlr3mbomlr3learners 0.13.0 compatibility
- 11mo agoggspatialterra becomes the default raster backend
- 11mo agomlr3mboMaintainer change and mlr3pipelines 0.9.0 upkeep
- 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 mlr3mbo?
Both compete on the same themes — r-stats — within Analytics. mlr3mbo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is ggspatial better than mlr3mbo?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3mbo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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 mlr3mbo?
Top mlr3mbo alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3mbo alternatives" section above for the current picks, or visit /alternatives/mlr3mbo for the full list with editorial commentary on each.