https://github.com/mhahsler/arulesviz

Visualizing Association Rules and Frequent Itemsets with R
https://github.com/mhahsler/arulesviz

arules association-rules cran frequent-itemsets interactive-visualizations r visualization

Last synced: 8 days ago
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Visualizing Association Rules and Frequent Itemsets with R

• Host: GitHub
• URL: https://github.com/mhahsler/arulesviz
• Owner: mhahsler
• Created: 2015-10-12T03:36:20.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2024-08-27T22:23:15.000Z (2 months ago)
• Last Synced: 2024-09-28T03:29:11.894Z (about 1 month ago)
• Topics: arules, association-rules, cran, frequent-itemsets, interactive-visualizations, r, visualization
• Language: R
• Homepage: http://mhahsler.github.io/arulesViz/
• Size: 31.1 MB
• Stars: 53
• Watchers: 8
• Forks: 15
• Open Issues: 3
• Metadata Files:
  • Readme: README.Rmd
  • Changelog: NEWS.md

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README

        
---

output: github_document

---

```{r echo=FALSE, results = 'asis'}

pkg <- "arulesViz"

source("https://raw.githubusercontent.com/mhahsler/pkg_helpers/main/pkg_helpers.R")

pkg_title(pkg)

```

## Introduction

This R package 

extends package [arules](https://github.com/mhahsler/arules) with various visualization techniques for association rules and itemsets. The package also includes several interactive visualizations for rule exploration.

```{r echo=FALSE, results = 'asis'}

pkg_usage(pkg)

pkg_citation(pkg, 2)

```

This might also require the development version of [arules](https://github.com/mhahsler/arules).

## Features

* Visualizations using engines `ggplot2` (default engine for most methods), `grid`, `base` (R base plots), `htmlwidget` (powered by `plotly` and `visNetwork`). 

* Interactive visualizations using `grid`, `plotly` and `visNetwork`.

* Interactive rule inspection with `datatable`.

* Integrated interactive rule exploration using `ruleExplorer`. 

Available Visualizations

* Scatterplot, two-key plot

* Matrix and matrix 3D visualization

* Grouped matrix-based visualization

* Several graph-based visualizations

* Doubledecker and mosaic plots

* Parallel Coordinate plot

```{r echo=FALSE, results = 'asis'}

pkg_install(pkg)

```

## Usage 

Mine some rules.

```{r }

library("arulesViz")

data("Groceries")

rules <- apriori(Groceries, parameter = list(support = 0.005, confidence = 0.5))

```

### Standard visualizations

```{r scatterplot}

plot(rules)

```

```{r graph}

plot(rules, method = "graph", limit = 20)

```

### Interactive visualization

Live examples for interactive visualizations can be seen in [Chapter 5 of An R Companion for Introduction to Data Mining](https://mhahsler.github.io/Introduction_to_Data_Mining_R_Examples/book/association-analysis-basic-concepts-and-algorithms.html#interactive-visualizations)

## References

* Michael Hahsler. [arulesViz: Interactive visualization of association rules with R.](https://journal.r-project.org/archive/2017/RJ-2017-047/RJ-2017-047.pdf) _R Journal,_ 9(2):163-175, December 2017.

* Michael Hahsler. [An R Companion for Introduction to Data Mining: Chapter 5](https://mhahsler.github.io/Introduction_to_Data_Mining_R_Examples/book/association-analysis-basic-concepts-and-algorithms.html). 

Online Book. https://mhahsler.github.io/Introduction_to_Data_Mining_R_Examples/book/, 2021.

* Michael Hahsler, Sudheer Chelluboina, Kurt Hornik, and Christian Buchta. [The arules R-package ecosystem: Analyzing interesting patterns from large transaction datasets.](https://jmlr.csail.mit.edu/papers/v12/hahsler11a.html) _Journal of Machine Learning Research,_ 12:1977-1981, 2011.

* Michael Hahsler and Sudheer Chelluboina. [Visualizing Association Rules: Introduction 

to the R-extension Package arulesViz](https://cran.r-project.org/package=arulesViz/vignettes/arulesViz.pdf) (with complete examples).