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tidymodels

rsample:General Resampling Infrastructure

Classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).

Maintained by Hannah Frick. Last updated 4 months ago.

20.0 match 341 stars 16.85 score 4.8k scripts 77 dependents

tidymodels

infer:Tidy Statistical Inference

The objective of this package is to perform inference using an expressive statistical grammar that coheres with the tidy design framework.

Maintained by Simon Couch. Last updated 4 months ago.

20.0 match 731 stars 15.65 score 3.4k scripts 16 dependents

tidymodels

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.

Maintained by Julia Silge. Last updated 8 days ago.

20.0 match 132 stars 11.16 score 146 scripts 13 dependents

tidymodels

modeldata:Data Sets Useful for Modeling Examples

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

Maintained by Max Kuhn. Last updated 3 months ago.

20.0 match 22 stars 10.88 score 2.1k scripts 14 dependents

tidymodels

usemodels:Boilerplate Code for 'Tidymodels' Analyses

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

Maintained by Max Kuhn. Last updated 3 months ago.

23.7 match 84 stars 6.90 score 134 scripts

ropensci

waywiser:Ergonomic Methods for Assessing Spatial Models

Assessing predictive models of spatial data can be challenging, both because these models are typically built for extrapolating outside the original region represented by training data and due to potential spatially structured errors, with "hot spots" of higher than expected error clustered geographically due to spatial structure in the underlying data. Methods are provided for assessing models fit to spatial data, including approaches for measuring the spatial structure of model errors, assessing model predictions at multiple spatial scales, and evaluating where predictions can be made safely. Methods are particularly useful for models fit using the 'tidymodels' framework. Methods include Moran's I ('Moran' (1950) <doi:10.2307/2332142>), Geary's C ('Geary' (1954) <doi:10.2307/2986645>), Getis-Ord's G ('Ord' and 'Getis' (1995) <doi:10.1111/j.1538-4632.1995.tb00912.x>), agreement coefficients from 'Ji' and Gallo (2006) (<doi: 10.14358/PERS.72.7.823>), agreement metrics from 'Willmott' (1981) (<doi: 10.1080/02723646.1981.10642213>) and 'Willmott' 'et' 'al'. (2012) (<doi: 10.1002/joc.2419>), an implementation of the area of applicability methodology from 'Meyer' and 'Pebesma' (2021) (<doi:10.1111/2041-210X.13650>), and an implementation of multi-scale assessment as described in 'Riemann' 'et' 'al'. (2010) (<doi:10.1016/j.rse.2010.05.010>).

Maintained by Michael Mahoney. Last updated 7 months ago.

spatialspatial-analysistidymodelstidyverse

10.5 match 38 stars 6.51 score 19 scripts

jameshwade

measure:A Recipes-style Interface to Tidymodels for Analytical Measurements

Analytical measurements...

Maintained by James Wade. Last updated 6 months ago.

recipestidymodels

12.9 match 5 stars 5.22 score 55 scripts

paithiov909

baritsu:Wrappers for 'mlpack'

A collection of wrappers for the 'mlpack' package that allows passing formula as their argument.

Maintained by Akiru Kato. Last updated 17 days ago.

tidymodels

10.0 match 3 stars 3.13 score 1 scripts