← Back to home
Comparison · Analytics

fastml vs fillpattern

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

fastml vs fillpattern: at a glance

Featurefastmlfillpattern
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesautoml, tidymodels, survival analysis, cross-validationggplot2, data-visualization, accessibility, graphics
Last editorial update41m ago1h ago
WebsiteVisit →Visit →

What is fastml?

fastml added survival modelling and leakage-proof resampling, moving past classification and regression.

A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.

Read the full fastml trajectory →

What is fillpattern?

Pattern fills for ggplot2, hardened against the ways users write sizes

fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.

Read the full fillpattern trajectory →

fastml vs fillpattern: editorial side-by-side

F
fastml
ANALYTICS
0.0

fastml added survival modelling and leakage-proof resampling, moving past classification and regression.

◆ Current state

A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.

◆ Where it's heading

The package is moving from convenience wrapper to something that has to be defensible statistically. Nested cross-validation, fold-wise rather than up-front imputation, and explicit leakage checks are all corrections to the shortcuts that make AutoML easy and its scores optimistic. Survival adds a third task type alongside classification and regression, and it arrived with its own metrics rather than being bolted onto the existing ones. Note the entry body is cut off at 8,000 characters, so the release is larger than what is shown.

◆ Prediction

Expect the remaining survival engines to fill in and the sandboxing of custom preprocessing to tighten, since both were still being iterated on within this same release's commit list.

F
fillpattern
ANALYTICS
0.0

Pattern fills for ggplot2, hardened against the ways users write sizes

◆ Current state

fillpattern provides pattern fills — stripes, bricks, dots — for ggplot2 and base R graphics, aimed at figures that must stay legible in greyscale or to colour-blind readers. The 1.0.3 release is mostly defensive: size modifier strings ending in a colon no longer swap width for height, modify_size() reports invalid units instead of crashing and understands in, inches and cm, and a background colour bug in scale_fill_pattern() is fixed. The minimum R version rises to 4.2.0 for recent graphics engine features.

◆ Where it's heading

Development is slow and entirely reactive to how the string-based size interface fails. The pattern across releases is the same: a user hits an edge — very small fill areas in 1.0.2, malformed unit strings in 1.0.3 — and the fix is either a graceful fallback or a clearer error. Leaning on R's newer graphics engine rather than reimplementing pattern rendering keeps the package small at the cost of raising its version floor.

◆ Prediction

Expect further releases to stay in the same register: parsing and validation fixes for the size and unit interface, with the pattern set itself unlikely to change.

Alternatives to fastml and fillpattern

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 fastml or fillpattern.

See all fastml alternatives → · See all fillpattern alternatives →

Recent activity from fastml and fillpattern

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

  1. 6mo agofillpatternSize string parsing fixed; invalid units now report instead of crash
  2. 8mo agofastmlVersion 0.7.5
  3. 1y agofastmlEngine-specific tuning, imbalance handling and explainability
  4. 1y agofastmlSingle-workflow evaluation fix
  5. 1y agofastmlVersion 0.5.0
  6. 2y agofillpatternSmall fill areas no longer crash; min_size falls back to solid
  7. 2y agofillpatternfillpattern 1.0.1

Frequently asked questions

What is the difference between fastml and fillpattern?

They serve adjacent needs but don't currently overlap on shipped themes. fastml and fillpattern 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 fastml better than fillpattern?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastml and fillpattern 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 fastml?

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

What are the best alternatives to fillpattern?

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