HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
Comparison · Infra & APIs
driveR vs MachineShop
A side-by-side editorial comparison of driveR and MachineShop — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-packagemachine-learning
driveR vs MachineShop: at a glance
What is driveR?
A cancer driver prioritization package that ships rarely and mostly to stay installable
driveR prioritizes cancer driver genes from somatic variant and copy number data, combining coding impact scores, noncoding impact, copy number alteration scores and hotspot annotations into a multi-task learning classification model. Version 0.5.0 added gene-level SCNA data frames as an accepted input to create_features_df(), with an example table shipped alongside, widening the entry point beyond the segment-level format. The same release moved org.Hs.eg.db and both hg19 and hg38 TxDb annotation packages from Imports to Suggests under new CRAN policy, with dependent functions now raising an error when they are absent rather than silently degrading.
What is MachineShop?
A mature R modelling framework refining variable importance and resampling controls
MachineShop provides a unified interface over a wide set of R model packages, handling fitting, resampling, performance metrics and variable importance behind one API. Recent releases are narrow and mostly corrective: 3.9.2 removed dead documentation links and fixed a Java parameter in a BART example, 3.9.1 ensured global settings reach compute nodes when varimp() runs in parallel and patched XGBoost model compatibility. The last release with real surface change was 3.9.0, which added offset support to XGBModel and a pool argument to calibration() controlling whether calibration curves are computed on pooled predictions or averaged across resampling iterations.
driveR vs MachineShop: editorial side-by-side
driveR
0.0INFRA · APIS
A cancer driver prioritization package that ships rarely and mostly to stay installable
◆ Current state
driveR prioritizes cancer driver genes from somatic variant and copy number data, combining coding impact scores, noncoding impact, copy number alteration scores and hotspot annotations into a multi-task learning classification model. Version 0.5.0 added gene-level SCNA data frames as an accepted input to create_features_df(), with an example table shipped alongside, widening the entry point beyond the segment-level format. The same release moved org.Hs.eg.db and both hg19 and hg38 TxDb annotation packages from Imports to Suggests under new CRAN policy, with dependent functions now raising an error when they are absent rather than silently degrading.
◆ Where it's heading
Releases are infrequent and split cleanly between capability and correction. GRCh38 support arrived in 0.4.0 and cancer-type-specific thresholds were refreshed in 0.3.0, while the 0.2.x pair fixed scoring errors serious enough to require retraining: a column name mismatch meant the SCNA score was not being computed at all, and MCR table coordinates needed converting from hg18 to hg19. Both times the bundled classification model and thresholds were rebuilt as a consequence. Since 0.4.0 the changes have been input handling and packaging rather than method.
◆ Prediction
The move of the annotation databases to Suggests suggests a leaner install is the current priority; the entries give no indication of planned model or scoring changes.
MachineShop
0.0INFRA · APIS
A mature R modelling framework refining variable importance and resampling controls
◆ Current state
MachineShop provides a unified interface over a wide set of R model packages, handling fitting, resampling, performance metrics and variable importance behind one API. Recent releases are narrow and mostly corrective: 3.9.2 removed dead documentation links and fixed a Java parameter in a BART example, 3.9.1 ensured global settings reach compute nodes when varimp() runs in parallel and patched XGBoost model compatibility. The last release with real surface change was 3.9.0, which added offset support to XGBModel and a pool argument to calibration() controlling whether calibration curves are computed on pooled predictions or averaged across resampling iterations.
◆ Where it's heading
Development has concentrated on variable importance and resampling rather than on adding models. 3.8.0 restructured the VariableImportance class to record which method and metric produced it, with an update() method to migrate objects from earlier versions, and extended term-specific p-values to Cox, POLR and survival regression models. 3.7.0 added grouped and stratified resampling to the control objects. The pace has slowed markedly - four releases in the last two years against six in the two before - and the recent content is compatibility work against XGBoost, parsnip, ggplot2 and recipes.
◆ Prediction
Expect the deprecated calibration pooling behaviour to be removed in a future release as the notes state, with the intervening versions continuing to track upstream model package changes.
Alternatives to driveR and MachineShop
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 driveR or MachineShop.
bsvarSIGNs
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
estimatr
Fast design-based estimators for experiments, coasting on CRAN patches.
ggdist
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
ipaddress
IP address vectors for R that hit 1.0 and then went quiet.
ltertools
A column-key toolkit for stitching decades of ecological field data into one table.
See all driveR alternatives → · See all MachineShop alternatives →
Recent activity from driveR and MachineShop
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 5mo agoMachineShopDocumentation link cleanup and a BART example fix
- 7mo agodriveRGene-level copy number input accepted, annotation packages made optional
- 8mo agoMachineShopGlobal settings now reach compute nodes during parallel varimp
- 1y agoMachineShopOffset support for XGBoost and per-iteration calibration curves
- 1y agoMachineShopVariable importance objects record their own method and metric
- 2y agoMachineShopGrouped and stratified resampling in the control objects
- 3y agodriveRCRAN documentation error fixed
- 3y agoMachineShopBackward compatibility for older model objects
- 4y agodriveRGRCh38 genome build supported
- 4y agodriveRCancer-type-specific thresholds updated
- 5y agodriveRMCR coordinates converted to hg19 and the model retrained
- 5y agodriveRCopy number score was never being computed, model rebuilt
Frequently asked questions
What is the difference between driveR and MachineShop?
Both compete on the same themes — r-package, machine-learning — within Infra & APIs. driveR and MachineShop 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 driveR better than MachineShop?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. driveR and MachineShop 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 driveR?
Top driveR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "driveR alternatives" section above for the current picks, or visit /alternatives/driver for the full list with editorial commentary on each.
What are the best alternatives to MachineShop?
Top MachineShop alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "MachineShop alternatives" section above for the current picks, or visit /alternatives/machineshop for the full list with editorial commentary on each.