Also Observe the change in number of rules for different support,confidence values
install.packages("rmarkdown",repos = "http://cran.us.r-project.org")
## Installing package into 'C:/Users/tswaminathan/Documents/R/win-library/3.5'
## (as 'lib' is unspecified)
## package 'rmarkdown' successfully unpacked and MD5 sums checked
##
## The downloaded binary packages are in
## C:\Users\tswaminathan\AppData\Local\Temp\Rtmpk9eYyC\downloaded_packages
install.packages("arules",repos = "http://cran.us.r-project.org")
## Installing package into 'C:/Users/tswaminathan/Documents/R/win-library/3.5'
## (as 'lib' is unspecified)
## package 'arules' successfully unpacked and MD5 sums checked
##
## The downloaded binary packages are in
## C:\Users\tswaminathan\AppData\Local\Temp\Rtmpk9eYyC\downloaded_packages
install.packages("arulesViz",repos = "http://cran.us.r-project.org")
## Installing package into 'C:/Users/tswaminathan/Documents/R/win-library/3.5'
## (as 'lib' is unspecified)
## package 'arulesViz' successfully unpacked and MD5 sums checked
##
## The downloaded binary packages are in
## C:\Users\tswaminathan\AppData\Local\Temp\Rtmpk9eYyC\downloaded_packages
# install.packages("rmarkdown")
# install.packages("arules")
# install.packages("arulesViz")
library(arules)
## Loading required package: Matrix
##
## Attaching package: 'arules'
## The following objects are masked from 'package:base':
##
## abbreviate, write
library(arulesViz)
## Loading required package: grid
book <- read.csv(file.choose())
View(book)
rules <- apriori(as.matrix(book),parameter=list(support=0.02, confidence = 0.5,minlen=5))
## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.02 5
## maxlen target ext
## 10 rules FALSE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 40
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[11 item(s), 2000 transaction(s)] done [0.00s].
## sorting and recoding items ... [11 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3 4 5 6 done [0.00s].
## writing ... [186 rule(s)] done [0.05s].
## creating S4 object ... done [0.00s].
# Provided the rules with 2 % Support, 50 % Confidence and Minimum to purchase
# 5 books
rules
## set of 186 rules
inspect(head(sort(rules, by = "lift")))
## lhs rhs support confidence
## [1] {CookBks,DoItYBks,ArtBks,ItalCook} => {ItalArt} 0.0250 0.6849315
## [2] {CookBks,ArtBks,GeogBks,ItalCook} => {ItalArt} 0.0240 0.6666667
## [3] {ChildBks,CookBks,ArtBks,ItalCook} => {ItalArt} 0.0285 0.6263736
## [4] {CookBks,ArtBks,GeogBks,ItalArt} => {ItalCook} 0.0240 0.9600000
## [5] {ChildBks,CookBks,ArtBks,ItalArt} => {ItalCook} 0.0285 0.9500000
## [6] {CookBks,DoItYBks,ArtBks,ItalArt} => {ItalCook} 0.0250 0.9259259
## lift count
## [1] 14.122299 50
## [2] 13.745704 48
## [3] 12.914920 57
## [4] 8.458150 48
## [5] 8.370044 57
## [6] 8.157938 50
head(quality(rules))
## support confidence lift count
## 1 0.020 1.0000000 2.320186 40
## 2 0.020 0.8695652 2.055710 40
## 3 0.020 1.0000000 4.662005 40
## 4 0.020 0.8888889 7.831620 40
## 5 0.025 1.0000000 2.320186 50
## 6 0.025 0.6666667 2.364066 50
plot(rules,method = "scatterplot")
## To reduce overplotting, jitter is added! Use jitter = 0 to prevent jitter.
plot(rules,method = "grouped")
# The Art books are being sold at a larger extent along with other Cook, art, geo, child books
# Cook books are also being sold at a larger extent along with other chld, art, geo, Doit books)
plot(rules,method = "graph")
## Warning: plot: Too many rules supplied. Only plotting the best 100 rules
## using 'support' (change control parameter max if needed)
