Machine Learning Models and Tools
Overview
Meta-package for statistical and machine learning with a unified interface for model fitting, prediction, performance assessment, and presentation of results. Approaches for model fitting and prediction of numerical, categorical, or censored time-to-event outcomes include traditional regression models, regularization methods, tree-based methods, support vector machines, neural networks, ensembles, data preprocessing, filtering, and model tuning and selection. Performance metrics are provided for model assessment and can be estimated with independent test sets, split sampling, cross-validation, or bootstrap resampling. Resample estimation can be executed in parallel for faster processing and nested in cases of model tuning and selection. Modeling results can be summarized with descriptive statistics; calibration curves; variable importance; partial dependence plots; confusion matrices; and ROC, lift, and other performance curves.
- Remove import of defunct **mboost** function
bns().
From NEWS.md in the release
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-07-03
Show 4 earlier changesHide 4 earlier changes
- ERROR11 OK, 2 ERROR2026-06-08
- OK14 OK2026-04-08
- ERROR13 OK, 1 ERROR2026-04-07
- OK14 OK2026-03-10
Documentation
- Help pages
- 97 (1 internal)includes a package overview page
- Examples that run
- 40%33 run in a plain check · 49 only when donttest examples are enabled (R CMD check --as-cran) · 1 never run
- Exported functions with examples
- 93%
- Documented parameters
- 88%
- Return-value docs
- 95%
- Help pages citing references
- 10%
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- 7
- Median days to close, 50 most recently updated closed PRs
- 4
Stars over time
Forks over time
Releases over time
Issues over time
PRs over time
3 development-tooling and community-health practices detected across 2 families in the upstream repository
Checks run against github.com/brian-j-smith/machineshop on 2026-10-18.
Dependencies
Installing MachineShop adds 84 packages (42 with compiled code, 67 MB of source tarballs). Heaviest: stringi 11 MB, TH.data 8.2 MB, ggplot2 6.0 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- 3.9.4Latest
- 3.9.32026-06-26 · diff ↗
- RR 4.6.0 released · 2026-04-24
- 3.9.22026-01-30 · diff ↗
- 3.9.12025-12-16 · diff ↗
- 3.9.02025-06-09 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 3.8.02024-08-19 · diff ↗
- RR 4.4.0 released · 2024-04-24
- 3.7.02023-09-18 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 3.6.22023-03-21 · diff ↗
- 3.6.12023-02-01 · diff ↗
- 3.6.0
- 3.5.0
- RR 4.2.0 released · 2022-04-22
Show 33 earlier eventsHide 33 earlier events
- 3.4.0
- 3.3.02022-02-09 · diff ↗ ·
added 7 exports
ModelSpecification, set_optim_bayes, set_optim_bfgs, set_optim_grid, set_optim_method, set_optim_pso, set_optim_sann - 3.2.0
- 3.1.02021-10-01 · diff ↗
- 3.0.02021-08-19 · diff ↗ ·
removed 1 export
MLControladded 5 exports
set_monitor, set_predict, set_strata, %>%, case_weights - 2.9.02021-06-18 · diff ↗
- RR 4.1.0 released · 2021-05-18
- 2.8.0
- 2.7.0
- unarchivedReturned to CRAN2021-01-26
- 2.6.12021-01-26 · diff ↗
- archivedRemoved from CRAN2021-01-20check problems were not corrected in time
- 2.6.0
- 2.5.0
- 2.4.02020-06-05 · diff ↗
- 2.3.02020-05-14 · diff ↗ ·
removed 5 exports
SelectedFormula, SelectedMatrix, SelectedModelFrame, SelectedRecipe, TunedRecipe - RR 4.0.0 released · 2020-04-24
- 2.2.02020-03-18 · diff ↗
- 2.1.02020-02-09 · diff ↗ ·
removed 2 exports
offset, tuneadded 9 exports
ModeledInput, SelectedInput, TunedInput, step_kmeans, step_kmedoids, step_spca, tunable.step_kmeans, tunable.step_kmedoids, tunable.step_spca - 2.0.02019-12-10 · diff ↗ ·
removed 7 exports
Calibration, Confusion, Curves, expand.model, Lift, Resamples, ModelListadded 16 exports
offset, role_binom, role_case, role_pred, role_surv, ParameterGrid, BinomialVariate, DiscreteVariate, NegBinomialVariate, PoissonVariate, SelectedFormula, SelectedMatrix, SelectedModelFrame, SelectedRecipe, as.MLModel, CVOptimismControl - 1.6.02019-10-11 · diff ↗ ·
added 6 exports
expand_model, expand_params, expand_steps, settings, TunedRecipe, ModelList - 1.5.0
- 1.4.0
- RR 3.6.0 released · 2019-04-26
- 1.3.02019-04-23 · diff ↗
- 1.2.02019-02-15 · diff ↗ ·
removed 1 export
modelmetricsadded 10 exports
Curves, performance_curve, SurvEvents, SurvProbs, auc, fnr, fpr, rpp, tnr, tpr - 1.1.0
- 1.0.02019-01-02 · diff ↗ ·
added 9 exports
expand.model, performance, gini, msle, rmsle, MLMetric, MLMetric<-, BARTMachineModel, LARSModel - 0.4.02018-12-13 · diff ↗ ·
added 40 exports
Calibration, Confusion, Lift, metricinfo, modelinfo, modelmetrics, accuracy, brier, cindex, cross_entropy, f_score, kappa2, mae, mse, npv, ppv, pr_auc, precision, r2, recall, rmse, roc_auc, roc_index, sensitivity, specificity, weighted_kappa2, MLControl, AdaBagModel, AdaBoostModel, BlackBoostModel and 10 more - 0.3.0
- 0.2.02018-11-19 · diff ↗ ·
added 13 exports
calibration, dependence, lift, ModelFrame, SplitControl, TrainControl, KNNModel, StackedModel, SuperModel, XGBModel, XGBDARTModel, XGBLinearModel, XGBTreeModel - 0.1-12018-10-14
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-10-14
- Total releases
- 38 / 8 yrs
- License
- GPL-3 OSI
- Additional repositories
- brian-j-smith.github.io
- Minimum R
- ≥ 4.1.0
- Bundled data
- 19 KB / 1 file
- Download size
- 1.4 MB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("MachineShop")The package provides a citation file that builds its entry when R runs it. Run citation() to see it.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.