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https://github.com/tidymodels/shinymodels

r r-package rstats shiny

Last synced: 19 days ago
JSON representation

Host: GitHub
URL: https://github.com/tidymodels/shinymodels
Owner: tidymodels
License: other
Created: 2021-06-03T04:19:47.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2024-10-24T16:46:09.000Z (about 2 months ago)
Last Synced: 2024-11-17T04:05:22.315Z (26 days ago)
Topics: r, r-package, rstats, shiny
Language: R
Homepage: https://shinymodels.tidymodels.org/
Size: 11.1 MB
Stars: 46
Watchers: 7
Forks: 5
Open Issues: 3
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md

Awesome Lists containing this project

jimsghstars - tidymodels/shinymodels - (R)

README

        ---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```

# shinymodels

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)

[![CRAN status](https://www.r-pkg.org/badges/version/shinymodels)](https://CRAN.R-project.org/package=shinymodels)

[![Codecov test coverage](https://codecov.io/gh/tidymodels/shinymodels/branch/main/graph/badge.svg)](https://app.codecov.io/gh/tidymodels/shinymodels?branch=main)

[![R-CMD-check](https://github.com/tidymodels/shinymodels/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/tidymodels/shinymodels/actions/workflows/R-CMD-check.yaml)

[![R-CMD-check-no-suggests](https://github.com/tidymodels/shinymodels/actions/workflows/R-CMD-check-no-suggests.yaml/badge.svg)](https://github.com/tidymodels/shinymodels/actions/workflows/R-CMD-check-no-suggests.yaml)

The goal of shinymodels is to launch a Shiny app given tidymodels' tuning or resampling results, to make it easier to explore the modeling results.

## Installation

You can install the released version of shinymodels from [CRAN](https://CRAN.R-project.org) with:

``` r

install.packages("shinymodels") 

```

And the development version from [GitHub](https://github.com/) with:

``` r

# install.packages("pak")

pak::pak("tidymodels/shinymodels")

```

## Example

Start by tuning or fitting to resampling folds, using tune functions like `fit_resamples()` or `tune_bayes()`.

As an example, we will simulate a simple relationship:

```{r load, include = FALSE}

library(shinymodels)

library(tidymodels)

tidymodels_prefer()

```

```{r}

library(shinymodels)

library(tidymodels)

tidymodels_prefer()

set.seed(1)

n <- 100

simulated <-

  data.frame(x1 = runif(n, min = -1), x2 = runif(n)) %>% 

  mutate(y = 3 - 5 * x1 + 15 * x1^2 +  + 10 * x2 + rnorm(n, sd = 5))

```

Let's resample a linear regression model that is missing an important nonlinear term (i.e., `poly(x1, 2)`):

```{r}

set.seed(2)

folds <- vfold_cv(simulated)

reg_res <-

  linear_reg() %>%

  fit_resamples(y ~ .,

                resamples = folds,

                control = control_resamples(save_pred = TRUE))

```

To interactively assess the model fit, we can use the  `explore()` function: 

```r

explore(reg_res)

```

Use the Shiny app to explore the model results and detect any outliers or problematic observations. In the image below, the observed and predicted values are visualized, with one sample selected and highlighted. The residuals are also plotted against `x1` and the quadratic pattern shows that a nonlinear term should be added.  

![screenshot of shiny app. Options are shown in a column to the left. In the main area 3 tabs are shown; Observed vs. Predicted, Residuals vs. Predicted, and Residals vs. A numeric predictor.](man/figures/example.png)

The `explore()` function can be used with objects produced by `fit_resamples()`, `last_fit()`, or any of the `tune_*()` functions. 

## Contributing

This project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.

- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on RStudio Community](https://community.rstudio.com/new-topic?category_id=15&tags=tidymodels,question).

- If you think you have encountered a bug, please [submit an issue](https://github.com/tidymodels/shinymodels/issues).

- Either way, learn how to create and share a [reprex](https://reprex.tidyverse.org/articles/articles/learn-reprex.html) (a minimal, reproducible example), to clearly communicate about your code.

- Check out further details on [contributing guidelines for tidymodels packages](https://www.tidymodels.org/contribute/) and [how to get help](https://www.tidymodels.org/help/).