← Back to home
Comparison · ai-assistants

doc2vec vs mlr3tuningspaces

A side-by-side editorial comparison of doc2vec and mlr3tuningspaces — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

doc2vec vs mlr3tuningspaces: at a glance

Featuredoc2vecmlr3tuningspaces
Sectorai-assistantsai-assistants
Velocity score0.02.5
Sparks · 30d00
Top themesnlp, embeddings, topic-modeling, r-packagehyperparameter-tuning, mlr3, benchmark-studies, r-package
Last editorial update1h ago9h ago
WebsiteVisit →Visit →

What is doc2vec?

doc2vec's one directional release added topic discovery to a document-embedding package

doc2vec wraps a C++ paragraph2vec implementation for R, training document and word embeddings from raw text. Its 0.2.0 release added the top2vec semantic clustering algorithm and support for initialising word embeddings from a pretrained set, which is where the package's current capability surface was set. Since then it has been quiet: the 2025 release only fixes a DOI in DESCRIPTION and drops the C++11 declaration from Makevars.

Read the full doc2vec trajectory →

What is mlr3tuningspaces?

A curated catalogue of published hyperparameter search spaces, now reaching deep neural networks

mlr3tuningspaces packages hyperparameter search spaces taken from published benchmark studies so mlr3 users can tune against a citable range instead of inventing bounds. Its release history is steady catalogue growth punctuated by compatibility bumps across the mlr3 stack. 0.7.0 adds spaces for deep neural networks from Gorishniy, Rubachev, Khrulkov and Babenko (2021) alongside mlr3 1.7.2 compatibility.

Read the full mlr3tuningspaces trajectory →

doc2vec vs mlr3tuningspaces: editorial side-by-side

D
doc2vec
AI-ASSISTANTS
0.0

doc2vec's one directional release added topic discovery to a document-embedding package

◆ Current state

doc2vec wraps a C++ paragraph2vec implementation for R, training document and word embeddings from raw text. Its 0.2.0 release added the top2vec semantic clustering algorithm and support for initialising word embeddings from a pretrained set, which is where the package's current capability surface was set. Since then it has been quiet: the 2025 release only fixes a DOI in DESCRIPTION and drops the C++11 declaration from Makevars.

◆ Where it's heading

This is a settled member of the bnosac NLP family and moves with it rather than on its own schedule. The same C++11 Makevars cleanup landed across word2vec and BTM within a day of this release, which is the shape of a CRAN compliance sweep over a maintainer's whole set rather than package-level development. Nothing in five years suggests further algorithm work is planned here.

◆ Prediction

Expect the next release to be another cross-package compliance pass triggered by a CRAN or toolchain change, not new modelling capability.

M
mlr3tuningspaces
AI-ASSISTANTS
2.5

A curated catalogue of published hyperparameter search spaces, now reaching deep neural networks

◆ Current state

mlr3tuningspaces packages hyperparameter search spaces taken from published benchmark studies so mlr3 users can tune against a citable range instead of inventing bounds. Its release history is steady catalogue growth punctuated by compatibility bumps across the mlr3 stack. 0.7.0 adds spaces for deep neural networks from Gorishniy, Rubachev, Khrulkov and Babenko (2021) alongside mlr3 1.7.2 compatibility.

◆ Where it's heading

The catalogue keeps widening one paper at a time — Kühn (2018) rbv1 spaces in 0.4.0, a corrected attribution to Binder, Pfisterer and Bischl (2020) for rbv2 in the same release, and now a deep-learning set in 0.7.0. That growth is bounded by forces outside the package: 0.6.0 had to delete the `kknn` spaces outright when the underlying package left CRAN, a breaking change driven by upstream availability rather than any design decision here.

◆ Prediction

Expect further spaces from newly published benchmark papers rather than a change in what the package does, since every feature release in this window has been of that form. Whether the deep-learning spaces get extended depends on learner support elsewhere in mlr3, which these entries do not cover.

Alternatives to doc2vec and mlr3tuningspaces

Other ai-assistants 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 doc2vec or mlr3tuningspaces.

See all doc2vec alternatives → · See all mlr3tuningspaces alternatives →

Recent activity from doc2vec and mlr3tuningspaces

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

  1. 21d agomlr3tuningspacesDeep neural network tuning spaces added
  2. 8mo agodoc2vecFix DESCRIPTION DOI; drop C++11 from Makevars
  3. 1y agomlr3tuningspaceskknn tuning spaces removed after CRAN departure
  4. 1y agomlr3tuningspacesCompatibility with mlr3learners 0.9.0
  5. 2y agomlr3tuningspacesCompatibility with mlr3tuning 1.0.0
  6. 2y agomlr3tuningspacesranger.rbv1 factor handling narrowed; paradox 1.0.0 support
  7. 3y agomlr3tuningspacesrbv1 search spaces added; rbv2 attribution corrected
  8. 5y agodoc2vectop2vec clustering and transfer learning from pretrained vectors
  9. 5y agodoc2vecValgrind fixes; WMD removed and udpipe suggestion dropped
  10. 5y agodoc2vecInitial release wrapping the hiyijian doc2vec implementation

Frequently asked questions

What is the difference between doc2vec and mlr3tuningspaces?

Both compete on the same themes — r-package — within ai-assistants. mlr3tuningspaces 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 doc2vec better than mlr3tuningspaces?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3tuningspaces 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 ai-assistants products to evaluate alongside.

What are the best alternatives to doc2vec?

Top doc2vec alternatives in ai-assistants are ranked by recent ship velocity. Browse the "doc2vec alternatives" section above for the current picks, or visit /alternatives/doc2vec for the full list with editorial commentary on each.

What are the best alternatives to mlr3tuningspaces?

Top mlr3tuningspaces alternatives in ai-assistants are ranked by recent ship velocity. Browse the "mlr3tuningspaces alternatives" section above for the current picks, or visit /alternatives/mlr3tuningspaces for the full list with editorial commentary on each.