README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
devtools::load_all() #todo
```
# tidyrules

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[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/tidyrules)](https://cran.r-project.org/package=tidyrules)
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> [tidyrules](https://cran.r-project.org/package=tidyrules) [R](https://www.r-project.org/) [package](https://cran.r-project.org/) provides a framework to work with decision rules. Rules can be extracted from supported models, augmented with (custom) metrics using validation data, manipulated using standard dataframe operations, reordered and pruned based on a metric, predict on unseen (test) data. Utilities include; Creating a rulelist manually, Exporting a rulelist as a SQL case statement and so on. The package offers two classes; rulelist and ruleset based on dataframe.

**website**: https://talegari.github.io/tidyrules/

![](man/figures/tidyrules_schematic.png)

## Example
<details>
<summary>expand/collapse</summary>

```{r example}
library(tidyrules)
```

```{r basic C5 example}
model_c5 = C50::C5.0(Species ~ ., data = iris, rules = TRUE)
pander::pandoc.table(tidy(model_c5), split.tables = 120)
```
</details>

## Installation
<details>
<summary>expand/collapse</summary>

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

```{r, eval = FALSE}
install.packages("tidyrules")
```

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

```{r, eval = FALSE}
# install.packages("devtools")
devtools::install_github("talegari/tidyrules")
```
</details>