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Comparison · Analytics
forecast vs mlr3filters
A side-by-side editorial comparison of forecast and mlr3filters — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-stats
forecast vs mlr3filters: at a glance
What is forecast?
After years of pure maintenance, forecast 9.0.0 reopens the package
forecast is the long-established R forecasting package that fable was meant to succeed. For several years its releases were RNG fixes, base-R compatibility and documentation. Then 9.0.0 arrived with a batch of new model constructors, wider prediction-interval support and a rewritten accuracy() built on S3 methods.
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.
forecast vs mlr3filters: editorial side-by-side
forecast
0.0ANALYTICS
After years of pure maintenance, forecast 9.0.0 reopens the package
◆ Current state
forecast is the long-established R forecasting package that fable was meant to succeed. For several years its releases were RNG fixes, base-R compatibility and documentation. Then 9.0.0 arrived with a batch of new model constructors, wider prediction-interval support and a rewritten accuracy() built on S3 methods.
◆ Where it's heading
The major version reframes forecast around explicit *_model() constructors — mean, random walk, spline, theta, Croston — rather than the older function-per-method style, and the 9.0.x patches since have been performance and argument-handling cleanups on top. That is an active maintenance line, not a package winding down in favour of fable.
◆ Prediction
Expect continued 9.0.x patches consolidating the new constructors and their forecast methods, with the older interfaces kept working alongside them.
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 forecast 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 forecast 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 forecast alternatives → · See all mlr3filters alternatives →
Recent activity from forecast and mlr3filters
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agomlr3filtersFilter dictionary listing now uses prototypes
- 4mo agoforecastFixes for checkresiduals() and mstl() lambda handling
- 5mo agoforecastFaster ARFIMA search and forecast.mlm() argument handling
- 7mo agoforecastforecast 9.0.0 adds five model constructors and rewrites accuracy() ⚡
- 11mo agomlr3filtersBoruta handles logical, factor and ordered features
- 1y agoforecastDocumentation and bug-fix release
- 2y agoforecastRNG state and base-R head/tail compatibility
- 2y agomlr3filtersBoruta and univariate Cox filters added
- 2y agoforecastMuch faster hfitted() for ARIMA and ETS models
- 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
Frequently asked questions
What is the difference between forecast and mlr3filters?
Both compete on the same themes — r-stats — within Analytics. forecast 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 forecast better than mlr3filters?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. forecast 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 forecast?
Top forecast alternatives in Analytics are ranked by recent ship velocity. Browse the "forecast alternatives" section above for the current picks, or visit /alternatives/forecast-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.