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dials vs themis

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

Shared themes:tidymodels

dials vs themis: at a glance

Featuredialsthemis
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themestidymodels, hyperparameters, deep-learning, grid-searchr, tidymodels, class-imbalance, resampling
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

What is dials?

dials is quietly registering the tuning parameters for tidymodels' deep-learning push

dials defines the parameter objects and grid constructors that tidymodels tunes over, which makes its release notes a reliable early read on what the rest of the stack is about to support. The last two releases are dominated by attention-model parameters — SAINT and tabular deep learning via brulee, TabPFN via parsnip's tab_pfn() — alongside catboost parameters for bonsai and calibration parameters for tailor.

Read the full dials trajectory →

What is themis?

themis is back to adding real resampling algorithms after a documentation-heavy stretch.

themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.

Read the full themis trajectory →

dials vs themis: editorial side-by-side

D
dials
ANALYTICS
0.0

dials is quietly registering the tuning parameters for tidymodels' deep-learning push

◆ Current state

dials defines the parameter objects and grid constructors that tidymodels tunes over, which makes its release notes a reliable early read on what the rest of the stack is about to support. The last two releases are dominated by attention-model parameters — SAINT and tabular deep learning via brulee, TabPFN via parsnip's tab_pfn() — alongside catboost parameters for bonsai and calibration parameters for tailor.

◆ Where it's heading

The grid machinery itself is settled: grid_space_filling() consolidated the older designs, and the grid_*() functions now error rather than warn on the wrong size argument. What keeps moving is the parameter catalog, and it is moving toward neural and foundation-model territory that tidymodels historically left alone. Error-message quality is a steady secondary theme.

◆ Prediction

Expect further parameter objects to land ahead of the parsnip and brulee releases that use them — the attention and tabular-foundation-model work in flight is the clearest thing the entries point to.

T
themis
ANALYTICS
2.5

themis is back to adding real resampling algorithms after a documentation-heavy stretch.

◆ Current state

themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.

◆ Where it's heading

The package grows by adding algorithms rather than restructuring itself. tomek() was rewritten to handle multiple classes and drop the unbalanced dependency, case weights arrived at 1.0.0, and cluster-centroid and condensed-nearest-neighbour under-sampling arrive now — each shipped as both a recipes step and a direct-implementation function.

◆ Prediction

Expect further under- and over-sampling methods in the same paired form, as the package fills out coverage of the standard class-imbalance literature.

Alternatives to dials and themis

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 dials or themis.

See all dials alternatives → · See all themis alternatives →

Recent activity from dials and themis

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

  1. 10d agothemisthemis 1.1.0 adds cluster-centroid and CNN under-sampling
  2. 1mo agodialsAttention and tabular deep-learning parameters for brulee models
  3. 4mo agodialsParameters for ordinal_reg() and the tab_pfn() foundation model
  4. 11mo agodialsprop_terms() for supervised feature selection recipes
  5. 1y agodialsCalibration method parameters for classification and regression
  6. 1y agodialsPostprocessing parameters added; grid size mismatches now error
  7. 1y agothemisthemis 1.0.3 corrects resampling direction in documentation
  8. 2y agodialsgrid_space_filling() consolidates the space-filling designs
  9. 2y agothemisthemis 1.0.2 makes internal consistency and speed changes
  10. 3y agothemisthemis 1.0.1 fixes upsampling errors when none is needed
  11. 4y agothemisthemis 1.0.0 adds case weights to up- and down-sampling
  12. 4y agothemisthemis 0.2.2 rewrites tomek() for multiclass, drops a dependency

Frequently asked questions

What is the difference between dials and themis?

Both compete on the same themes — tidymodels — within Analytics. themis 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 dials better than themis?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. themis 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 Analytics products to evaluate alongside.

What are the best alternatives to dials?

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

What are the best alternatives to themis?

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