Description
Visualizing Association Rules and Frequent Itemsets.
Description
Extends package 'arules' with various visualization techniques for association rules and itemsets. The package also includes several interactive visualizations for rule exploration. Michael Hahsler (2017) <doi:10.32614/RJ-2017-047>.
README.md
R package arulesViz - Visualizing Association Rules and Frequent Itemsets
This R package extends package arules with various visualization techniques for association rules and itemsets. The package also includes several interactive visualizations for rule exploration.
Installation
Stable CRAN version: Install from within R with
install.packages("arulesViz")
Current development version: Install from r-universe.
install.packages("arulesViz", repos = "https://mhahsler.r-universe.dev")
This might also require the development version of arules.
Features
- Visualizations using engines
ggplot2
(default engine for most methods),grid
,base
(R base plots),htmlwidget
(powered byplotly
andvisNetwork
). - Interactive visualizations using
grid
,plotly
andvisNetwork
. - 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
Usage
Mine some rules.
library("arulesViz")
data("Groceries")
rules <- apriori(Groceries, parameter = list(support = 0.005, confidence = 0.5))
## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.005 1
## maxlen target ext
## 10 rules TRUE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 49
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[169 item(s), 9835 transaction(s)] done [0.00s].
## sorting and recoding items ... [120 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3 4 done [0.00s].
## writing ... [120 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].
Standard visualizations
plot(rules)
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
References
- Michael Hahsler. arulesViz: Interactive visualization of association rules with R.R Journal, 9(2):163-175, December 2017.
- Michael Hahsler. An R Companion for Introduction to Data Mining: Chapter 5. 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.Journal of Machine Learning Research, 12:1977-1981, 2011.
- Michael Hahsler and Sudheer Chelluboina. Visualizing Association Rules: Introduction to the R-extension Package arulesViz (with complete examples).