fastml
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
A side-by-side editorial comparison of randomwalk and tglkmeans — release velocity, themes, recent moves, and the top alternatives to consider.
randomwalk spent every release getting an R simulation to run in the browser, not on a server.
A random walk and fractal-growth simulation package whose entire visible history is about its browser deployment. Six releases in four weeks moved a Shinylive dashboard from a blank black page to a working app — WebAssembly mounted from GitHub releases, CORS resolved by same-origin serving, missing plotting dependencies installed in-browser, then an async version using crew workers with its own debug log. A correctness fix followed, adding termination-position validation so simulations stop producing isolated pixels, and the most recent release publishes the package itself as a webR binary repository.
A k-means implementation that just told users their Spearman clustering on missing data was wrong
tglkmeans is a multi-core k-means implementation with seeding, aimed at single-cell and other large matrix workloads. Version 0.4.0 flipped the id_column default and moved to R's random number generator, 0.5.x added count-matrix downsampling and fixed id handling, and 0.6.3 in May 2026 is a correctness release: Spearman distance was ranking missing values as the largest value instead of dropping them, and predict_tgl_kmeans() with Euclidean distance did not reproduce the training metric when a cluster center had a missing dimension.
A random walk and fractal-growth simulation package whose entire visible history is about its browser deployment. Six releases in four weeks moved a Shinylive dashboard from a blank black page to a working app — WebAssembly mounted from GitHub releases, CORS resolved by same-origin serving, missing plotting dependencies installed in-browser, then an async version using crew workers with its own debug log. A correctness fix followed, adding termination-position validation so simulations stop producing isolated pixels, and the most recent release publishes the package itself as a webR binary repository.
The package is being built as a browser artifact first and an R package second: the readme, the vignettes and the release notes all point at a hosted dashboard rather than at library(). The last release completes that by making the compiled WebAssembly build installable by anyone via webr::install(), which turns the deployment work into something reusable outside this project. Version numbers are unreliable here — v0.2.0 was published two weeks after v1.0.2 — so read the dates, not the tags.
With the webR repository published, the next work most likely moves back to the simulation itself, though the entries give no direct evidence of planned features.
tglkmeans is a multi-core k-means implementation with seeding, aimed at single-cell and other large matrix workloads. Version 0.4.0 flipped the id_column default and moved to R's random number generator, 0.5.x added count-matrix downsampling and fixed id handling, and 0.6.3 in May 2026 is a correctness release: Spearman distance was ranking missing values as the largest value instead of dropping them, and predict_tgl_kmeans() with Euclidean distance did not reproduce the training metric when a cluster center had a missing dimension.
The package handles missing data across three distance metrics, and 0.6.3 shows those paths had drifted apart — Spearman behaved unlike Euclidean and Pearson, and prediction behaved unlike training. Both fixes change results on affected data, and the release notes are careful to bound exactly where: Spearman on data with NAs changes, complete data does not. Performance work runs alongside, with the dense per-thread vote matrix removed from the reassignment step.
With the metric paths now aligned on missing-value handling, further work is more likely to target the parallel reassignment internals than the distance semantics.
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 randomwalk or tglkmeans.
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
abclass built out angle-based classifiers in 2022, then went quiet except for CRAN upkeep.
churon is spending its entire release history getting a Rust ONNX binding through CRAN.
firatheme woke up after four years and started fixing what ggplot2 changed underneath it.
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
rainette rebuilt its Reinert clustering in 0.2.0, tuned it in 0.3.0, and has coasted since.
See all randomwalk alternatives → · See all tglkmeans alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. randomwalk and tglkmeans 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. randomwalk and tglkmeans 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.
Top randomwalk alternatives in Analytics are ranked by recent ship velocity. Browse the "randomwalk alternatives" section above for the current picks, or visit /alternatives/randomwalk for the full list with editorial commentary on each.
Top tglkmeans alternatives in Analytics are ranked by recent ship velocity. Browse the "tglkmeans alternatives" section above for the current picks, or visit /alternatives/tglkmeans for the full list with editorial commentary on each.