tidytext
Finished, widely taught, and shipping roxygen fixes.
Comparison · Analytics
lime vs mlr3filters
A side-by-side editorial comparison of lime and mlr3filters — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:machine-learningr-stats
lime vs mlr3filters: at a glance
What is lime?
lime survives on compatibility patches years after its research moment
lime brings local interpretable model-agnostic explanations to R. Its substantive development finished around 0.5.0 in 2019, which added argument pass-through to predict(), a gower_pow tuning knob and a batch of fixes. Since then there have been three releases: a namespace fix, a maintainer handover to Emil Hvitfeldt with general upkeep, and a patch to work across xgboost versions.
What is mlr3filters?
mlr3filters grows one feature-selection filter at a time
mlr3filters provides feature-filter methods to mlr3. Its releases follow a consistent shape: one or two new filters, broader feature-type support on existing ones, and error-message work. Boruta and a univariate Cox filter arrived in 0.8.0; 0.9.0 extended Boruta to logical, factor and ordered features and moved param_set to an active binding.
lime vs mlr3filters: editorial side-by-side
lime
0.0ANALYTICS
lime survives on compatibility patches years after its research moment
◆ Current state
lime brings local interpretable model-agnostic explanations to R. Its substantive development finished around 0.5.0 in 2019, which added argument pass-through to predict(), a gower_pow tuning knob and a batch of fixes. Since then there have been three releases: a namespace fix, a maintainer handover to Emil Hvitfeldt with general upkeep, and a patch to work across xgboost versions.
◆ Where it's heading
The package is in custodial maintenance — kept installable and compatible with the model packages it explains, rather than developed. The 2022 handover is the most consequential entry in the window because it determined that the package would keep getting patches at all.
◆ Prediction
Expect the next release to be another compatibility fix triggered by an upstream model package, not new explanation methods.
mlr3filters
0.0ANALYTICS
mlr3filters grows one feature-selection filter at a time
◆ Current state
mlr3filters provides feature-filter methods to mlr3. Its releases follow a consistent shape: one or two new filters, broader feature-type support on existing ones, and error-message work. Boruta and a univariate Cox filter arrived in 0.8.0; 0.9.0 extended Boruta to logical, factor and ordered features and moved param_set to an active binding.
◆ Where it's heading
This is incremental infrastructure that tracks mlr3's own conventions — cli printing, prototype-based dictionaries, featureless learners as defaults — while slowly widening which data types each filter accepts. Nothing in the recent history suggests a change of scope.
◆ Prediction
Expect another filter or two plus continued feature-type broadening, keeping pace with mlr3 core conventions.
Alternatives to lime and mlr3filters
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 lime or mlr3filters.
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 lime alternatives → · See all mlr3filters alternatives →
Recent activity from lime and mlr3filters
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agomlr3filtersFilter dictionary listing now uses prototypes
- 8mo agolimeCompatibility across all xgboost versions
- 11mo agomlr3filtersBoruta handles logical, factor and ordered features
- 2y agomlr3filtersBoruta and univariate Cox filters added
- 3y agomlr3filtersMissing-value tagging and wider CarScore feature support
- 3y agomlr3filtersMissing-value checks and featureless learner defaults
- 3y agomlr3filtersSurvival CAR score filter and pipeline documentation
- 3y agolimeMaintainer handover to Emil Hvitfeldt
- 5y agolimeorder() fix and lighter dependencies
- 6y agolimeNamespace fix following glmnet changes
- 7y agolimeexplain() gains pass-through args and gower_pow tuning
- 8y agolimeh2o support, NA handling and date feature types
Frequently asked questions
What is the difference between lime and mlr3filters?
Both compete on the same themes — machine-learning, r-stats — within Analytics. lime and mlr3filters 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 lime better than mlr3filters?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. lime and mlr3filters 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 lime?
Top lime alternatives in Analytics are ranked by recent ship velocity. Browse the "lime alternatives" section above for the current picks, or visit /alternatives/lime-r for the full list with editorial commentary on each.
What are the best alternatives to mlr3filters?
Top mlr3filters alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3filters alternatives" section above for the current picks, or visit /alternatives/mlr3filters for the full list with editorial commentary on each.