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fastml vs slope

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

Shared themes:cross-validation

fastml vs slope: at a glance

Featurefastmlslope
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesautoml, tidymodels, survival analysis, cross-validationsparse-regression, penalized-models, cpp, r-package
Last editorial update41m ago4h 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 slope?

A year after gutting itself for a C++ rewrite, SLOPE is back to polishing the interface

SLOPE fits sorted L-one penalized regression models. In July 2025 it replaced its entire solver with the external libslope C++ library, removing the ADMM solver, dropping debugging fields, changing alpha scaling and warning users directly that the breakage was extensive. The releases since have rebuilt convenience on top of that core: summary() and refit() methods for cross-validated objects, automatic refitting in cvSLOPE(), and a threading default reduced from half the available cores to one.

Read the full slope trajectory →

fastml vs slope: 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.

S
slope
ANALYTICS
0.0

A year after gutting itself for a C++ rewrite, SLOPE is back to polishing the interface

◆ Current state

SLOPE fits sorted L-one penalized regression models. In July 2025 it replaced its entire solver with the external libslope C++ library, removing the ADMM solver, dropping debugging fields, changing alpha scaling and warning users directly that the breakage was extensive. The releases since have rebuilt convenience on top of that core: summary() and refit() methods for cross-validated objects, automatic refitting in cvSLOPE(), and a threading default reduced from half the available cores to one.

◆ Where it's heading

The arc runs rewrite, then repair, then convenience. The 1.2.0 release is the repair phase — coefficients_scaled was returning unscaled values, which silently affected every coef.SLOPE() call — and 2.0.0 onward is convenience, with refit() now working without re-supplying training data. The tag timestamps are non-monotonic: 1.0.1 is stamped a minute after 1.1.0 despite the lower version, so ordering here reflects when tags were pushed, not what superseded what.

◆ Prediction

With the cross-validation workflow now closing itself out through automatic refitting, further work is more likely to extend the summary and plotting surface than to touch the solver again.

Alternatives to fastml and slope

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 slope.

See all fastml alternatives → · See all slope alternatives →

Recent activity from fastml and slope

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

  1. 2mo agosloperefit() defaults to training data; class-mismatch scoring fixed
  2. 6mo agoslopeCross-validation now refits automatically and gains summary methods
  3. 8mo agofastmlVersion 0.7.5
  4. 9mo agoslopeSingle-threaded by default, interruptible, and a scaling bug fixed
  5. 9mo agoslopeM1 Mac test fix
  6. 9mo agoslopeGlioma gene expression dataset added
  7. 1y agofastmlEngine-specific tuning, imbalance handling and explainability
  8. 1y agoslopeSLOPE 1.0.0
  9. 1y agofastmlSingle-workflow evaluation fix
  10. 1y agofastmlVersion 0.5.0

Frequently asked questions

What is the difference between fastml and slope?

Both compete on the same themes — cross-validation — within Analytics. fastml and slope 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 slope?

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

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