mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
A side-by-side editorial comparison of mlr3filters and tidytext — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Finished, widely taught, and shipping roxygen fixes.
tidytext is the package that made unnest_tokens() and the tidy-data approach to text analysis standard, and it has reached the point where its releases contain nothing to announce. The last three are roxygen package anchors, alt text on vignette figures, and a single bug fix in one stm tidier. The most recent substantive changes were in 0.4.0 and 0.3.3 — stm tidiers for high FREX and lift words, a labels function for scale_x_reordered(), and support for tidying STM models that use content covariates.
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.
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.
Expect another filter or two plus continued feature-type broadening, keeping pace with mlr3 core conventions.
tidytext is the package that made unnest_tokens() and the tidy-data approach to text analysis standard, and it has reached the point where its releases contain nothing to announce. The last three are roxygen package anchors, alt text on vignette figures, and a single bug fix in one stm tidier. The most recent substantive changes were in 0.4.0 and 0.3.3 — stm tidiers for high FREX and lift words, a labels function for scale_x_reordered(), and support for tidying STM models that use content covariates.
The direction is stability, and the release triggers are external. quanteda releases force updates to the dfm tidiers, a Matrix release forces another, tokenizers deprecating its tweet tokenizer forces removal of the tweet-specific functions here, and CRAN's Rd anchor requirement produces a release of its own. Nothing in the recent stream suggests new capability is planned, and for a package this embedded in teaching material that is a defensible position rather than a problem.
The entries do not support predicting new features. The likely next release is another compatibility update prompted by quanteda, stm, or a CRAN documentation requirement.
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 mlr3filters or tidytext.
mlr3proba is shedding weight as its survival work moves into sibling packages
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk swallowed anomalize whole, then went quiet for two years
modelbased is turning marginal effects into a full contrast grammar
easystats' parameters package absorbs one more model class every few weeks
See all mlr3filters alternatives → · See all tidytext alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. mlr3filters and tidytext 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3filters and tidytext 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.
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.
Top tidytext alternatives in Analytics are ranked by recent ship velocity. Browse the "tidytext alternatives" section above for the current picks, or visit /alternatives/tidytext for the full list with editorial commentary on each.