caret - Classification and Regression Training

Misc functions for training and plotting classification and regression models.

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19.04 score 1.7k stars 333 dependents 79k scripts 173k downloads

recipes - Preprocessing and Feature Engineering Steps for Modeling

A recipe prepares your data for modeling. We provide an extensible framework for pipeable sequences of feature engineering steps provides preprocessing tools to be applied to data. Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting processed output can then be used as inputs for statistical or machine learning models.

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18.30 score 614 stars 425 dependents 9.5k scripts 178k downloads

tidymodels - Easily Install and Load the 'Tidymodels' Packages

The tidy modeling "verse" is a collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.

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16.98 score 815 stars 15 dependents 74k scripts 133k downloads

parsnip - A Common API to Modeling and Analysis Functions

A common interface is provided to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. 'R', 'Spark', 'Stan', 'H2O', etc).

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16.57 score 652 stars 83 dependents 3.6k scripts 48k downloads

tune - Tidy Tuning Tools

The ability to tune models is important. 'tune' contains functions and classes to be used in conjunction with other 'tidymodels' packages for finding reasonable values of hyper-parameters in models, preprocessing methods, and post-processing steps.

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14.73 score 334 stars 50 dependents 1.2k scripts 38k downloads

Cubist - Rule- And Instance-Based Regression Modeling

Regression modeling using rules with added instance-based corrections.

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13.15 score 45 stars 19 dependents 3.0k scripts 25k downloads

stacks - Tidy Model Stacking

Model stacking is an ensemble technique that involves training a model to combine the outputs of many diverse statistical models, and has been shown to improve predictive performance in a variety of settings. 'stacks' implements a grammar for 'tidymodels'-aligned model stacking.

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12.40 score 302 stars 2 dependents 1.1k scripts 5.8k downloads

probably - Tools for Post-Processing Predicted Values

Models can be improved by post-processing class probabilities, by: recalibration, conversion to hard probabilities, assessment of equivocal zones, and other activities. 'probably' contains tools for conducting these operations as well as calibration tools and conformal inference techniques for regression models.

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12.35 score 121 stars 1 dependents 19k scripts 7.4k downloads

butcher - Model Butcher

Provides a set of S3 generics to axe components of fitted model objects and help reduce the size of model objects saved to disk.

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12.30 score 138 stars 17 dependents 216 scripts 11k downloads

C50 - C5.0 Decision Trees and Rule-Based Models

C5.0 decision trees and rule-based models for pattern recognition that extend the work of Quinlan (1993, ISBN:1-55860-238-0).

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12.13 score 53 stars 11 dependents 1.7k scripts 15k downloads

modeldata - Data Sets Useful for Modeling Examples

Data sets used for demonstrating or testing model-related packages are contained in this package.

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11.06 score 24 stars 17 dependents 2.1k scripts 38k downloads

finetune - Additional Functions for Model Tuning

The ability to tune models is important. 'finetune' enhances the 'tune' package by providing more specialized methods for finding reasonable values of model tuning parameters. Two racing methods described by Kuhn (2014) <doi:10.48550/arXiv.1405.6974> are included. An iterative search method using generalized simulated annealing (Bohachevsky, Johnson and Stein, 1986) <doi:10.1080/00401706.1986.10488128> is also included.

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9.82 score 64 stars 2 dependents 1.0k scripts 5.6k downloads

tailor - Iterative Steps for Postprocessing Model Predictions

Postprocessors refine predictions outputted from machine learning models to improve predictive performance or better satisfy distributional limitations. This package introduces 'tailor' objects, which compose iterative adjustments to model predictions. A number of pre-written adjustments are provided with the package, such as calibration. See Lichtenstein, Fischhoff, and Phillips (1977) <doi:10.1007/978-94-010-1276-8_19>. Other methods and utilities to compose new adjustments are also included. Tailors are tightly integrated with the 'tidymodels' framework.

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9.36 score 16 stars 51 dependents 33 scripts 31k downloads

tidyposterior - Bayesian Analysis to Compare Models using Resampling Statistics

Bayesian analysis used here to answer the question: "when looking at resampling results, are the differences between models 'real'?" To answer this, a model can be created were the performance statistic is the resampling statistics (e.g. accuracy or RMSE). These values are explained by the model types. In doing this, we can get parameter estimates for each model's affect on performance and make statistical (and practical) comparisons between models. The methods included here are similar to Benavoli et al (2017) <https://jmlr.org/papers/v18/16-305.html>.

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8.18 score 103 stars 295 scripts 623 downloads

brulee - High-Level Modeling Functions with 'torch'

Provides high-level modeling functions to define and train models using the 'torch' R package. Models include linear, logistic, and multinomial regression as well as multilayer perceptrons.

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7.91 score 73 stars 212 scripts 1.2k downloads

AmesHousing - The Ames Iowa Housing Data

Raw and processed versions of the data from De Cock (2011) <http://ww2.amstat.org/publications/jse> are included in the package.

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7.82 score 15 stars 2 dependents 644 scripts 5.7k downloads

modeldb - Fits Models Inside the Database

Uses 'dplyr' and 'tidyeval' to fit statistical models inside the database. It currently supports KMeans and linear regression models.

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databasedbplyrdplyrggplot2modelingrlangsqltidyevalvisualization

7.59 score 78 stars 63 scripts 582 downloads

AppliedPredictiveModeling - Functions and Data Sets for 'Applied Predictive Modeling'

A few functions and several data set for the Springer book 'Applied Predictive Modeling'.

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7.15 score 35 stars 1.3k scripts 6.1k downloads

baguette - Efficient Model Functions for Bagging

Tree- and rule-based models can be bagged (<doi:10.1007/BF00058655>) using this package and their predictions equations are stored in an efficient format to reduce the model objects size and speed.

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7.00 score 28 stars 802 scripts 848 downloads

usemodels - Boilerplate Code for 'Tidymodels' Analyses

Code snippets to fit models using the tidymodels framework can be easily created for a given data set.

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6.78 score 87 stars 174 scripts 302 downloads

desirability2 - Desirability Functions for Multiparameter Optimization

In-line functions for multivariate optimization via desirability functions (Derringer and Suich, 1980, <doi:10.1080/00224065.1980.11980968>) with easy use within 'dplyr' pipelines.

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6.73 score 14 stars 2 dependents 51 scripts 614 downloads

sfd - Space-Filling Design Library

A collection of pre-optimized space-filling designs, for up to ten parameters, is contained here. Functions are provided to access designs described by Husslage et al (2011) <doi:10.1007/s11081-010-9129-8> and Wang and Fang (2005) <doi:10.1142/9789812701190_0040>. The design types included are Audze-Eglais, MaxiMin, and uniform.

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6.48 score 70 dependents 6 scripts 29k downloads

plsmod - Model Wrappers for Projection Methods

Bindings for additional regression models for use with the 'parsnip' package, including ordinary and spare partial least squares models for regression and classification (Rohart et al (2017) <doi:10.1371/journal.pcbi.1005752>).

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mixomics

5.95 score 14 stars 90 scripts 446 downloads

shinymodels - Interactive Assessments of Models

Launch a 'shiny' application for 'tidymodels' results. For classification or regression models, the app can be used to determine if there is lack of fit or poorly predicted points.

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shiny

5.92 score 50 stars 48 scripts 284 downloads

tabpfn - Prior-Data Fitted Network Foundational Model for Tabular Data

Provides a consistent API for classification and regression models based on the 'TabPFN' model of Hollmann et al. (2025), "Accurate predictions on small data with a tabular foundation model," Nature, 637(8045) <doi:10.1038/s41586-024-08328-6>. The calculations are served via 'Python' to train and predict the model.

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5.88 score 33 stars 19 scripts 721 downloads

sparseLDA - Sparse Discriminant Analysis

Performs sparse linear discriminant analysis for Gaussians and mixture of Gaussian models.

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5.82 score 7 stars 2 dependents 40 scripts 4.0k downloads

desirability - Function Optimization and Ranking via Desirability Functions

S3 classes for multivariate optimization using the desirability function by Derringer and Suich (1980).

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5.26 score 3 stars 1 dependents 40 scripts 590 downloads

sparsediscrim - Sparse and Regularized Discriminant Analysis

A collection of sparse and regularized discriminant analysis methods intended for small-sample, high-dimensional data sets. The package features the High-Dimensional Regularized Discriminant Analysis classifier from Ramey et al. (2017) <arXiv:1602.01182>. Other classifiers include those from Dudoit et al. (2002) <doi:10.1198/016214502753479248>, Pang et al. (2009) <doi:10.1111/j.1541-0420.2009.01200.x>, and Tong et al. (2012) <doi:10.1093/bioinformatics/btr690>.

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5.18 score 3 stars 1 dependents 101 scripts 3.4k downloads

important - Supervised Feature Selection

Interfaces for choosing important predictors in supervised regression, classification, and censored regression models. Permuted importance scores (Biecek and Burzykowski (2021) <doi:10.1201/9780429027192>) can be computed for 'tidymodels' model fits.

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5.09 score 19 stars 26 scripts 199 downloads

beans - Data on Dried Beans

These data contain morphological image measurements for dried beans from Koklu and Ozkan (2020) <doi:10.1016/j.compag.2020.105507>.

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3.59 score 1 stars 78 scripts 319 downloads

QSARdata - Quantitative Structure Activity Relationship (QSAR) Data Sets

Molecular descriptors and outcomes for several public domain data sets

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3.34 score 70 scripts 3.2k downloads