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mlr3spatial vs waywiser

A side-by-side editorial comparison of mlr3spatial and waywiser — release velocity, themes, recent moves, and the top alternatives to consider.

mlr3spatial vs waywiser: at a glance

Featuremlr3spatialwaywiser
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmlr3, spatial, raster, predictionspatial-statistics, model-assessment, tidymodels, cran-compliance
Last editorial update4h ago1h ago
WebsiteVisit →Visit →

What is mlr3spatial?

Raster prediction in mlr3 finally returns class probabilities, not just hard labels.

mlr3spatial connects mlr3 learners to raster and vector spatial data, handling chunked prediction over large rasters through DataBackendRaster. Development is slow and fix-heavy: most releases in the last two years were compatibility work against mlr3 and paradox rather than new capability. 0.7.0 is the exception.

Read the full mlr3spatial trajectory →

What is waywiser?

Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.

waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.

Read the full waywiser trajectory →

mlr3spatial vs waywiser: editorial side-by-side

M
mlr3spatial
ANALYTICS
0.0

Raster prediction in mlr3 finally returns class probabilities, not just hard labels.

◆ Current state

mlr3spatial connects mlr3 learners to raster and vector spatial data, handling chunked prediction over large rasters through DataBackendRaster. Development is slow and fix-heavy: most releases in the last two years were compatibility work against mlr3 and paradox rather than new capability. 0.7.0 is the exception.

◆ Where it's heading

The package tracks the mlr3 core rather than leading it — 0.5.0 and 0.6.1 exist to absorb upstream changes in paradox and mlr3. Against that background, 0.7.0 adding probability predictions to predict_spatial() is the first genuine capability increase in a while, arriving alongside two DataBackendRaster fixes for multi-band sources and similarly-named layers. Cadence is roughly one release per year.

◆ Prediction

Given the pattern, the next release is more likely to be compatibility work against a new mlr3 or terra version than another feature; further raster-backend edge cases around layer naming are the visible loose end.

W
waywiser
ANALYTICS
0.0

Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.

◆ Current state

waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.

◆ Where it's heading

The package has reached the point where the interesting bugs are cross-platform and cross-package rather than statistical. Its main function, ww_multi_scale(), has been the focus of nearly every release since 0.4.0, working through units handling, aggregation ordering, raster inputs and metric-type dispatch. The dependency on vip and the tidymodels metric machinery means a share of releases exist only to track breaking changes elsewhere.

◆ Prediction

Expect the next substantive release to continue on ww_multi_scale() edge cases, given that it has absorbed most of the fixes in this window. The recent run of CRAN-compliance patches suggests no feature work is currently in flight.

Alternatives to mlr3spatial and waywiser

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 mlr3spatial or waywiser.

See all mlr3spatial alternatives → · See all waywiser alternatives →

Recent activity from mlr3spatial and waywiser

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agomlr3spatialpredict_spatial() gains probability predictions
  2. 10mo agomlr3spatialCompatibility with mlr3 1.2.0
  3. 1y agomlr3spatialError on conflicting X/Y columns in sf objects
  4. 1y agowaywiserStops downloading data during CRAN checks
  5. 1y agowaywiserVignettes no longer write to CRAN directories
  6. 1y agowaywiserKeeps the R version floor below 4.1
  7. 2y agowaywiserNaN results become NA; raster metrics dispatch correctly
  8. 2y agomlr3spatialCompatibility with paradox 1.0.0
  9. 2y agowaywiserGuards against ignored grid arguments; faster on sf data
  10. 2y agowaywiserFixes wrong observation counts and ignored grid units
  11. 3y agomlr3spatialUse terra::inMemory() instead of the @ptr slot
  12. 3y agomlr3spatialspatial_predict() accepts stars, sf and Raster* inputs

Frequently asked questions

What is the difference between mlr3spatial and waywiser?

They serve adjacent needs but don't currently overlap on shipped themes. mlr3spatial and waywiser 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 mlr3spatial better than waywiser?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3spatial and waywiser 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 mlr3spatial?

Top mlr3spatial alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3spatial alternatives" section above for the current picks, or visit /alternatives/mlr3spatial for the full list with editorial commentary on each.

What are the best alternatives to waywiser?

Top waywiser alternatives in Analytics are ranked by recent ship velocity. Browse the "waywiser alternatives" section above for the current picks, or visit /alternatives/waywiser for the full list with editorial commentary on each.