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fairmodels vs OHPL

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

fairmodels vs OHPL: at a glance

FeaturefairmodelsOHPL
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesfairness auditing, bias detection, dalex, r packagechemometrics, variable-selection, spectroscopy, archival-maintenance
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is fairmodels?

fairmodels sits dormant for three years, resurfacing only to satisfy a CRAN check.

fairmodels audits classification models for bias, built around fairness_check() and parity-loss metrics on top of DALEX explainers. The last substantive work dates from 2021; the 2025 release is a single-line change swapping ifelse for if/else in fairness_heatmap. Version 0.2.2 set the package's core design when it superseded metric differences with ratios.

Read the full fairmodels trajectory →

What is OHPL?

A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.

OHPL implements ordered homogeneity pursuit lasso, a variable selection method for high-dimensional spectroscopic data that groups correlated predictors before applying a lasso. The functional package was complete by 1.2 in 2017, when prediction, performance evaluation and simulated data generation functions were added. Every release since has touched documentation and packaging only.

Read the full OHPL trajectory →

fairmodels vs OHPL: editorial side-by-side

F
fairmodels
ANALYTICS
0.0

fairmodels sits dormant for three years, resurfacing only to satisfy a CRAN check.

◆ Current state

fairmodels audits classification models for bias, built around fairness_check() and parity-loss metrics on top of DALEX explainers. The last substantive work dates from 2021; the 2025 release is a single-line change swapping ifelse for if/else in fairness_heatmap. Version 0.2.2 set the package's core design when it superseded metric differences with ratios.

◆ Where it's heading

The release history describes a package that reached its intended shape early and has been custodial since — the gap from August 2022 to October 2025 carries no functional change at all. What movement exists is CRAN-driven: documentation compliance, example runtimes, coding-style notes. The fairness metrics themselves have not changed since the parity_loss corrections of 2020.

◆ Prediction

On this cadence the next release is most likely another CRAN-prompted one-liner rather than new fairness metrics; nothing in these entries points to active development.

O
OHPL
ANALYTICS
0.0

A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.

◆ Current state

OHPL implements ordered homogeneity pursuit lasso, a variable selection method for high-dimensional spectroscopic data that groups correlated predictors before applying a lasso. The functional package was complete by 1.2 in 2017, when prediction, performance evaluation and simulated data generation functions were added. Every release since has touched documentation and packaging only.

◆ Where it's heading

This is a published-method package in the archival phase: the algorithm is fixed, the paper is cited, and the maintainer keeps it installable. The releases read as a timeline of R packaging conventions rather than of the method — tidyverse code style in 2019, roxygen2 Markdown and bibentry() in 2024, Rd HTML validation in 2026. Gaps of two to five years between releases are normal here.

◆ Prediction

Expect the next release whenever CRAN introduces another documentation or packaging check; there is no indication the method itself will be extended.

Alternatives to fairmodels and OHPL

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 fairmodels or OHPL.

See all fairmodels alternatives → · See all OHPL alternatives →

Recent activity from fairmodels and OHPL

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

  1. 4mo agoOHPLRd documentation HTML validation fixed
  2. 9mo agofairmodelsOne-line fix in fairness_heatmap
  3. 2y agoOHPLDocumentation modernized to current R conventions
  4. 3y agofairmodelsCRAN compliance fixes and citation update
  5. 4y agofairmodelsCRAN v1.2.0
  6. 5y agofairmodelsCRAN v1.1.0
  7. 5y agofairmodelsDocumentation fixes and trimmed example runtimes
  8. 5y agofairmodelsCorrects parity_loss in the cutoff functions
  9. 7y agoOHPLCode restyled and repository links updated
  10. 9y agoOHPLCitation information and documentation site updated
  11. 9y agoOHPLPrediction and evaluation functions complete the package

Frequently asked questions

What is the difference between fairmodels and OHPL?

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

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

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

What are the best alternatives to OHPL?

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