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Comparison · Infra & APIs

cvms vs fdacluster

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

Shared themes:r-package

cvms vs fdacluster: at a glance

Featurecvmsfdacluster
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themescross-validation, r-package, model-evaluation, visualizationfunctional-data-analysis, clustering, r-package, rcpp
Last editorial update1h ago52m ago
WebsiteVisit →Visit →

What is cvms?

A cross-validation package whose real development has moved to its plotting function

cvms runs repeated cross-validation over model formulas and reports comparable metrics. The 2.0.0 release was a breaking correctness fix: every function accepting fold_cols mismatched training and testing data when fold indices were non-sequential, did not start at 1, or were strings, because the iteration index was compared against the raw fold value rather than its factor level index. 2.0.1 restored coefficient extraction for nnet::multinom and mixed models by supplying an environment containing the training data, and followed lme4's move of findbars() into the reformulas package.

Read the full cvms trajectory →

What is fdacluster?

Functional data clustering grew from one algorithm into a comparable suite

fdacluster clusters functional data while separating amplitude from phase variation, aligning curves as part of the clustering rather than before it. The algorithm set covers k-means, hierarchical clustering and DBSCAN, all producing a common caps result object so runs can be compared directly. Version 0.4.0 tightened the interface with is_domain_interval and transformation arguments describing the input data, added compatibility checking between incompatible option combinations, and split the L2 and normalized L2 distances into separate C++ classes to enforce that plain L2 cannot be combined with dilation or affine warping it is not invariant to.

Read the full fdacluster trajectory →

cvms vs fdacluster: editorial side-by-side

C
cvms
INFRA · APIS
0.0

A cross-validation package whose real development has moved to its plotting function

◆ Current state

cvms runs repeated cross-validation over model formulas and reports comparable metrics. The 2.0.0 release was a breaking correctness fix: every function accepting fold_cols mismatched training and testing data when fold indices were non-sequential, did not start at 1, or were strings, because the iteration index was compared against the raw fold value rather than its factor level index. 2.0.1 restored coefficient extraction for nnet::multinom and mixed models by supplying an environment containing the training data, and followed lme4's move of findbars() into the reformulas package.

◆ Where it's heading

Two threads run in parallel and only one is about cross-validation. The plotting function plot_confusion_matrix() has absorbed most feature work since 1.5.0 - custom gradient palettes, intensity limits, per-tile settings, dynamic font colors keyed to value thresholds, and arguments that accept functions rather than constants - to the point where a companion web application exists for using it without code. The cross-validation core, by contrast, sees maintenance: upstream compatibility fixes for pROC, ggnewscale and ggplot2, and the fold-matching correction that finally forced a major version.

◆ Prediction

Expect continued option growth in the confusion matrix plotting surface, since that is where nearly every release since 1.5.0 has spent its changes, with core cross-validation changes arriving only as upstream packages force them.

F
fdacluster
INFRA · APIS
0.0

Functional data clustering grew from one algorithm into a comparable suite

◆ Current state

fdacluster clusters functional data while separating amplitude from phase variation, aligning curves as part of the clustering rather than before it. The algorithm set covers k-means, hierarchical clustering and DBSCAN, all producing a common caps result object so runs can be compared directly. Version 0.4.0 tightened the interface with is_domain_interval and transformation arguments describing the input data, added compatibility checking between incompatible option combinations, and split the L2 and normalized L2 distances into separate C++ classes to enforce that plain L2 cannot be combined with dilation or affine warping it is not invariant to.

◆ Where it's heading

The trajectory runs from method implementation toward guardrails and portability. Early releases added capability; recent ones prevent misuse and reduce weight - dplyr, forcats, tidyr and purrr removed in 0.4.0, furrr swapped for future.apply - while 0.4.2 is entirely C++ correctness, replacing Armadillo's whole-object finiteness check with scalar std::isfinite and fixing an integer overflow in linear index computation that broke large datasets. Cadence is roughly one release a year.

◆ Prediction

Given that the last two releases were dependency reduction and numerical correctness rather than method work, expect the next to continue in that vein unless a new clustering algorithm is contributed.

Alternatives to cvms and fdacluster

Other Infra & APIs 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 cvms or fdacluster.

See all cvms alternatives → · See all fdacluster alternatives →

Recent activity from cvms and fdacluster

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

  1. 2mo agocvmsCoefficient extraction restored for multinom and mixed models
  2. 7mo agofdaclusterInteger overflow fixed for large datasets, C++ finiteness checks corrected
  3. 9mo agocvmsBreaking fix for mismatched folds with non-sequential fold IDs
  4. 11mo agocvmsTest compatibility with pROC 1.19 and a deprecation warning fix
  5. 1y agocvmsConfusion matrix fonts and colors can now be computed from the values
  6. 1y agocvmsTile intensity by row or column percentages
  7. 1y agofdaclusterParallel worker setup and an acronym correction
  8. 1y agocvmsMultinom coefficient extraction fix after a parameters update
  9. 1y agofdaclusterInput description arguments and enforced distance-warping compatibility
  10. 3y agofdaclusterMedian centroids and centroids defined on unioned grids
  11. 3y agofdaclusterNamespace notation and optional dependency guards
  12. 3y agofdaclusterHierarchical clustering, DBSCAN and a shared result class arrive together

Frequently asked questions

What is the difference between cvms and fdacluster?

Both compete on the same themes — r-package — within Infra & APIs. cvms and fdacluster 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 cvms better than fdacluster?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cvms and fdacluster 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to cvms?

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

What are the best alternatives to fdacluster?

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