Other packages > Find by keyword >

MachineShop  

Machine Learning Models and Tools
View on CRAN: Click here


Download and install MachineShop package within the R console
Install from CRAN:
install.packages("MachineShop")

Install from Github:
library("remotes")
install_github("cran/MachineShop")

Install by package version:
library("remotes")
install_version("MachineShop", "3.9.1")



Attach the package and use:
library("MachineShop")
Maintained by
Brian J Smith
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-10-14
Latest Update: 2025-06-09
Description:
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.
How to cite:
Brian J Smith (2018). MachineShop: Machine Learning Models and Tools. R package version 3.9.1, https://cran.r-project.org/web/packages/MachineShop. Accessed 20 Aug. 2026.
Previous versions and publish date:
0.1-1 (2018-10-14 17:30), 0.2.0 (2018-11-19 17:30), 0.3.0 (2018-11-23 12:20), 0.4.0 (2018-12-13 00:20), 1.0.0 (2019-01-02 15:30), 1.1.0 (2019-01-23 15:10), 1.2.0 (2019-02-15 17:20), 1.3.0 (2019-04-23 16:00), 1.4.0 (2019-06-08 06:20), 1.5.0 (2019-08-01 19:30), 1.6.0 (2019-10-11 00:30), 2.0.0 (2019-12-10 23:40), 2.1.0 (2020-02-09 00:50), 2.2.0 (2020-03-18 16:40), 2.3.0 (2020-05-14 01:40), 2.4.0 (2020-06-05 00:40), 2.5.0 (2020-08-06 01:10), 2.6.0 (2021-01-19 20:20), 2.6.1 (2021-01-26 18:40), 2.7.0 (2021-03-02 20:10), 2.8.0 (2021-04-16 18:50), 2.9.0 (2021-06-18 10:20), 3.0.0 (2021-08-19 22:20), 3.1.0 (2021-10-01 16:00), 3.2.0 (2021-12-06 16:10), 3.3.0 (2022-02-09 14:20), 3.4.0 (2022-03-16 13:30), 3.5.0 (2022-06-03 10:40), 3.6.0 (2022-09-05 17:20), 3.6.1 (2023-02-01 19:40), 3.6.2 (2023-03-21 14:00), 3.7.0 (2023-09-18 16:00), 3.8.0 (2024-08-19 19:40), 3.9.0 (2025-06-09 21:10), 3.9.1 (2025-12-16 07:20), 3.9.2 (2026-01-30 16:40), (2026-07-09 08:10)
Other packages that cited MachineShop R package
View MachineShop citation profile
Other R packages that MachineShop depends, imports, suggests or enhances
Complete documentation for MachineShop
Functions, R codes and Examples using the MachineShop R package
Some associated functions: AdaBagModel . AdaBoostModel . BARTMachineModel . BARTModel . BlackBoostModel . C50Model . CForestModel . CoxModel . DiscreteVariate . EarthModel . FDAModel . GAMBoostModel . GBMModel . GLMBoostModel . GLMModel . GLMNetModel . ICHomes . KNNModel . LARSModel . LDAModel . LMModel . MDAModel . MLControl . MLMetric . MLModel . MachineShop-package . ModelFrame-methods . ModelSpecification-methods . NNetModel . NaiveBayesModel . PLSModel . POLRModel . ParameterGrid . ParsnipModel . QDAModel . RFSRCModel . RPartModel . RandomForestModel . RangerModel . SVMModel . SelectedInput . SelectedModel . StackedModel . SuperModel . SurvMatrix . SurvRegModel . TreeModel . TunedInput . TunedModel . TuningGrid . XGBModel . as.MLInput . as.MLModel . as.data.frame . calibration . case_weights . combine-methods . confusion . dependence . diff-methods . expand_model . expand_modelgrid-methods . expand_params . expand_steps . extract-methods . fit-methods . inputs . lift . metricinfo . metrics . modelinfo . models . performance . performance_curve . plot-methods . predict . print-methods . quote . recipe_roles . reexports . resample-methods . response-methods . rfe-methods . set_monitor-methods . set_optim-methods . set_predict . set_strata . settings . step_kmeans . step_kmedoids . step_lincomp . step_sbf . step_spca . summary-methods . t.test . unMLModelFit . varimp . 
Some associated R codes: MLControl.R . MLInput.R . MLMetric.R . MLModel.R . MLOptimization.R . ML_AdaBagModel.R . ML_AdaBoostModel.R . ML_BARTMachineModel.R . ML_BARTModel.R . ML_BlackBoostModel.R . ML_C50Model.R . ML_CForestModel.R . ML_CoxModel.R . ML_EarthModel.R . ML_FDAModel.R . ML_GAMBoostModel.R . ML_GBMModel.R . ML_GLMBoostModel.R . ML_GLMModel.R . ML_GLMNetModel.R . ML_KNNModel.R . ML_LARSModel.R . ML_LDAModel.R . ML_LMModel.R . ML_MDAModel.R . ML_NNetModel.R . ML_NaiveBayesModel.R . ML_PLSModel.R . ML_POLRModel.R . ML_ParsnipModel.R . ML_QDAModel.R . ML_RFSRCModel.R . ML_RPartModel.R . ML_RandomForestModel.R . ML_RangerModel.R . ML_SVMModel.R . ML_StackedModel.R . ML_SuperModel.R . ML_SurvRegModel.R . ML_TreeModel.R . ML_XGBModel.R . MachineShop-package.R . ModelFrame.R . ModelRecipe.R . ModelSpecification.R . TrainedInputs.R . TrainedModels.R . TrainingParams.R . append.R . calibration.R . case_comps.R . classes.R . coerce.R . combine.R . conditions.R . confusion.R . convert.R . data.R . dependence.R . diff.R . expand.R . extract.R . fit.R . grid.R . metricinfo.R . metrics.R . metrics_factor.R . metrics_numeric.R . modelinfo.R . models.R . performance.R . performance_curve.R . plot.R . predict.R . print.R . recipe_roles.R . reexports.R . resample.R . response.R . rfe.R . settings.R . step_kmeans.R . step_kmedoids.R . step_lincomp.R . step_sbf.R . step_spca.R . summary.R . survival.R . utils.R . varimp.R .  Full MachineShop package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

mapaccuracy  
Unbiased Thematic Map Accuracy and Area
Unbiased estimators of overall and per-class thematic map accuracy and area published in Olofsson et ...
Download / Learn more Package Citations See dependency  
rfishbase  
R Interface to 'FishBase'
A programmatic interface to 'FishBase', re-written based on an accompanying 'RESTful' API. Access t ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
ggtea  
Palettes and Themes for 'ggplot2'
A collection of palettes and themes for 'ggplot2', offering a light, pastel aesthetic. Syntax follow ...
Download / Learn more Package Citations See dependency  
Brundle  
Normalisation Tools for Inter-Condition Variability of ChIP-Seq Data
Inter-sample condition variability is a key challenge of normalising ChIP-seq data. This implementat ...
Download / Learn more Package Citations See dependency  
AsthmaNHANES  
Asthma Data Sets from NHANES
Data sets and examples from National Health and Nutritional Examination Survey (NHANES). ...
Download / Learn more Package Citations See dependency  

28,313

R Packages

239,283

Dependencies

75,034

Author Associations

28,314

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA